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fix(curriculum): convert all video challenges to markdown (#39189)

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Shaun Hamilton
2020-08-04 20:56:41 +01:00
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14
curriculum/challenges/english/07-scientific-computing-with-python/python-for-everybody/iterations-loop-idioms.english.md
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@ -8,14 +8,16 @@ videoId: AelGAcoMXbI
---
## Description
<section id='description'>
</section>
## Tests
<section id='tests'>
```yml
````yml
question:
text: |
Below is code to find the smallest value from a list of values. One line has an error that will cause the code to not work as expected. Which line is it?:
@ -31,14 +33,14 @@ question:
```
answers:
- |
3
3
- |
4
4
- |
6
6
- |
7
7
solution: 3
```
````
</section>

8
curriculum/challenges/english/07-scientific-computing-with-python/python-for-everybody/more-conditional-structures.english.md
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@ -34,13 +34,13 @@ question:
answers:
- |
1
1
- |
3
3
- |
3,4
3,4
- |
4
4
- |
None
solution: 3

19
curriculum/challenges/english/08-data-analysis-with-python/data-analysis-with-python-course/data-analysis-example-a.english.md
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@ -7,24 +7,31 @@ videoId: nVAaxZ34khk
---
## Description
<section id='description'>
More resources:
- <a href="https://notebooks.ai/rmotr-curriculum/freecodecamp-pandas-real-life-example-24fa5bf8" target='_blank'>Notebook</a>
</section>
## Tests
<section id='tests'>
```yml
question:
text: 'What does the shape of our dataframe tell us?'
text: |
What does the shape of our dataframe tell us?
answers:
- 'The size in gigabytes the dataframe we loaded into memory is.'
- 'How many rows and columns our dataframe has.'
- 'How many rows the source data had before loading.'
- 'How many columns the source data had before loading.'
- |
The size in gigabytes the dataframe we loaded into memory is.
- |
How many rows and columns our dataframe has.
- |
How many rows the source data had before loading.
- |
How many columns the source data had before loading.
solution: 2
```
</section>

15
curriculum/challenges/english/08-data-analysis-with-python/data-analysis-with-python-course/data-analysis-example-b.english.md
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@ -7,21 +7,28 @@ videoId: 0kJz0q0pvgQ
---
## Description
<section id='description'>
More resources:
- <a href="https://notebooks.ai/rmotr-curriculum/freecodecamp-pandas-real-life-example-24fa5bf8" target='_blank'>Notebook</a>
</section>
## Tests
<section id='tests'>
```yml
question:
text: 'What does the <code>loc</code> method allow you to do?'
text: |
What does the <code>loc</code> method allow you to do?
answers:
- 'Retrieve a subset of rows and columns by supplying interger-location arguments.'
- 'Access a group of rows and columns by supplying label(s) arguments.'
- 'Returns the first <code>n</code> rows based on the integer argument supplied.'
- |
Retrieve a subset of rows and columns by supplying interger-location arguments.
- |
Access a group of rows and columns by supplying label(s) arguments.
- |
Returns the first <code>n</code> rows based on the integer argument supplied.
solution: 2
```

21
curriculum/challenges/english/08-data-analysis-with-python/data-analysis-with-python-course/data-cleaning-and-visualizations.english.md
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@ -7,23 +7,32 @@ videoId: mHjxzFS5_Z0
---
## Description
<section id='description'>
More resources:
- <a href="https://notebooks.ai/rmotr-curriculum/data-cleaning-rmotr-freecodecamp-fd76fa59" target='_blank'>Notebook</a>
</section>
## Tests
<section id='tests'>
```yml
````yml
question:
text: |
When using Matplotlib's global API, what does the order of numbers mean here?: `plt.subplot(1, 2, 1)`
When using Matplotlib's global API, what does the order of numbers mean here?
```py
plt.subplot(1, 2, 1)
```
answers:
- 'My figure will have one column, two rows, and I am going to start drawing in the first (left) plot.'
- 'I am going to start drawing in the first (left) plot, my figure will have two rows, and my figure will have one column.'
- 'My figure will have one row, two columns, and I am going to start drawing in the first (left) plot.'
- |
My figure will have one column, two rows, and I am going to start drawing in the first (left) plot.
- |
I am going to start drawing in the first (left) plot, my figure will have two rows, and my figure will have one column.
- |
My figure will have one row, two columns, and I am going to start drawing in the first (left) plot.
solution: 3
```
````
</section>

12
curriculum/challenges/english/08-data-analysis-with-python/data-analysis-with-python-course/data-cleaning-duplicates.english.md
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@ -7,22 +7,28 @@ videoId: kj7QqjXhH6A
---
## Description
<section id='description'>
More resources:
- <a href="https://notebooks.ai/rmotr-curriculum/data-cleaning-rmotr-freecodecamp-fd76fa59" target='_blank'>Notebook</a>
</section>
## Tests
<section id='tests'>
```yml
question:
text: |
The Python method `.duplicated()` returns a boolean Series for your DataFrame. `True` is the return value for rows that:
answers:
- contain a duplicate, where the value for the row contains the first occurrence of that value.
- contain a duplicate, where the value for the row is at least the second occurrence of that value.
- contain a duplicate, where the value for the row contains either the first or second occurrence.
- |
contain a duplicate, where the value for the row contains the first occurrence of that value.
- |
contain a duplicate, where the value for the row is at least the second occurrence of that value.
- |
contain a duplicate, where the value for the row contains either the first or second occurrence.
solution: 2
```

12
curriculum/challenges/english/08-data-analysis-with-python/data-analysis-with-python-course/data-cleaning-introduction.english.md
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@ -7,18 +7,20 @@ videoId: ovYNhnltVxY
---
## Description
<section id='description'>
More resources:
- <a href="https://notebooks.ai/rmotr-curriculum/data-cleaning-rmotr-freecodecamp-fd76fa59" target='_blank'>Notebook</a>
</section>
## Tests
<section id='tests'>
```yml
````yml
question:
text: |
What will the following code print out?:
What will the following code print out?
```py
import pandas as pd
@ -30,7 +32,8 @@ question:
```
answers:
- '3'
- |
3
- |
```
0 True
@ -50,7 +53,6 @@ question:
dtype: bool
```
solution: 1
```
````
</section>

9
curriculum/challenges/english/08-data-analysis-with-python/data-analysis-with-python-course/data-cleaning-with-dataframes.english.md
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@ -7,18 +7,20 @@ videoId: sTMN_pdI6S0
---
## Description
<section id='description'>
More resources:
- <a href="https://notebooks.ai/rmotr-curriculum/data-cleaning-rmotr-freecodecamp-fd76fa59" target='_blank'>Notebook</a>
</section>
## Tests
<section id='tests'>
```yml
````yml
question:
text: |
What will the following code print out?:
What will the following code print out?
```py
import pandas as pd
@ -59,7 +61,6 @@ question:
dtype: float64
```
solution: 2
```
````
</section>

16
curriculum/challenges/english/08-data-analysis-with-python/data-analysis-with-python-course/how-to-use-jupyter-notebooks-intro.english.md
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@ -7,6 +7,7 @@ videoId: h8caJq2Bb9w
---
## Description
<section id='description'>
More resources:
- <a href="https://notebooks.ai/rmotr-curriculum/interactive-jupyterlab-tutorial-ac5fa63f" target='_blank'>Notebook</a>
@ -14,17 +15,22 @@ More resources:
</section>
## Tests
<section id='tests'>
```yml
question:
text: What is *not* allowed in a Jupyter Notebook's cell?
text: |
What is **not** allowed in a Jupyter Notebook's cell?
answers:
- "Markdown"
- "Python code"
- "An Excel sheet"
- |
Markdown
- |
Python code
- |
An Excel sheet
solution: 3
```
</section>

19
curriculum/challenges/english/08-data-analysis-with-python/data-analysis-with-python-course/introduction-to-data-analysis.english.md
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@ -7,24 +7,31 @@ videoId: VJrP2FUzKP0
---
## Description
<section id='description'>
More resources:
- <a href="https://docs.google.com/presentation/d/1fDpjlyMiOMJyuc7_jMekcYLPP2XlSl1eWw9F7yE7byk" target='_blank'>Slides</a>
</section>
## Tests
<section id='tests'>
```yml
question:
text: "Why should you choose R over Python for data analysis?"
text: |
Why should you choose R over Python for data analysis?
answers:
- "It's simple to learn."
- "It's better at dealing with advanced statistical methods."
- "There are many powerful libraries that support R."
- "It's free and open source."
- |
It's simple to learn.
- |
It's better at dealing with advanced statistical methods.
- |
There are many powerful libraries that support R.
- |
It's free and open source.
solution: 2
```
</section>

16
curriculum/challenges/english/08-data-analysis-with-python/data-analysis-with-python-course/jupyter-notebooks-cells.english.md
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@ -7,6 +7,7 @@ videoId: 5PPegAs9aLA
---
## Description
<section id='description'>
More resources:
- <a href="https://notebooks.ai/rmotr-curriculum/interactive-jupyterlab-tutorial-ac5fa63f" target='_blank'>Notebook</a>
@ -14,17 +15,22 @@ More resources:
</section>
## Tests
<section id='tests'>
```yml
question:
text: <pre>Which cells are responsible for rich display?</pre>
text: |
Which cells are responsible for rich display?
answers:
- Code Cells
- Markdown Cells
- Raw Cells
- |
Code Cells
- |
Markdown Cells
- |
Raw Cells
solution: 1
```
</section>

22
curriculum/challenges/english/08-data-analysis-with-python/data-analysis-with-python-course/jupyter-notebooks-importing-and-exporting-data.english.md
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@ -7,6 +7,7 @@ videoId: k1msxD3JIxE
---
## Description
<section id='description'>
More resources:
- <a href="https://notebooks.ai/rmotr-curriculum/interactive-jupyterlab-tutorial-ac5fa63f" target='_blank'>Notebook</a>
@ -14,19 +15,26 @@ More resources:
</section>
## Tests
<section id='tests'>
```yml
question:
text: "What kind of data can you import and work with in a Jupyter Notebook?"
text: |
What kind of data can you import and work with in a Jupyter Notebook?
answers:
- "Excel files."
- "CSV files."
- "XML files."
- "Data from an API."
- "All of the above."
- |
Excel files.
- |
CSV files.
- |
XML files.
- |
Data from an API.
- |
All of the above.
solution: 5
```
</section>

18
curriculum/challenges/english/08-data-analysis-with-python/data-analysis-with-python-course/numpy-algebra-and-size.english.md
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@ -7,22 +7,30 @@ videoId: XAT97YLOKD8
---
## Description
<section id='description'>
More resources:
- <a href="https://notebooks.ai/rmotr-curriculum/freecodecamp-intro-to-numpy-6c285b74" target='_blank'>Notebook</a>
</section>
## Tests
<section id='tests'>
```yml
question:
text: What is the relationship between size of objects (such as lists and datatypes) in memory in Python's standard library and the NumPy library? Knowing this, what are the implications for performance?
text: |
What is the relationship between size of objects (such as lists and datatypes) in memory in Python's standard library and the NumPy library? Knowing this, what are the implications for performance?
answers:
- Standard Python objects take up much more memory to store than NumPy objects; operations on comparable standard Python and NumPy objects complete in roughly the same time.
- NumPy objects take up much more memory than standard Python objects; operations on NumPy objects complete very quickly compared to comparable objects in standard Python.
- NumPy objects take up much less memory than Standard Python objects; operations on Standard Python objects complete very quickly compared to comparable objects on NumPy Object.
- Standard Python objects take up more memory than NumPy objects; operations on NumPy objects complete very quickly compared to comparable objects in standard Python.
- |
Standard Python objects take up much more memory to store than NumPy objects; operations on comparable standard Python and NumPy objects complete in roughly the same time.
- |
NumPy objects take up much more memory than standard Python objects; operations on NumPy objects complete very quickly compared to comparable objects in standard Python.
- |
NumPy objects take up much less memory than Standard Python objects; operations on Standard Python objects complete very quickly compared to comparable objects on NumPy Object.
- |
Standard Python objects take up more memory than NumPy objects; operations on NumPy objects complete very quickly compared to comparable objects in standard Python.
solution: 4
```

16
curriculum/challenges/english/08-data-analysis-with-python/data-analysis-with-python-course/numpy-arrays.english.md
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@ -7,18 +7,20 @@ videoId: VDYVFHBL1AM
---
## Description
<section id='description'>
More resources:
- <a href="https://notebooks.ai/rmotr-curriculum/freecodecamp-intro-to-numpy-6c285b74" target='_blank'>Notebook</a>
</section>
## Tests
<section id='tests'>
```yml
````yml
question:
text: |
What will the following code print out?:
What will the following code print out?
```py
A = np.array([
@ -31,21 +33,23 @@ question:
```
answers:
- "[['a' 'b']]"
- |
```python
[['a' 'b']]
```
- |
```py
[['b' 'c']
['e' 'f']
['h' 'i']]
```
- |
```
```py
[['a' 'b']
['d' 'e']
['g' 'h']]
```
solution: 3
```
````
</section>

29
curriculum/challenges/english/08-data-analysis-with-python/data-analysis-with-python-course/numpy-boolean-arrays.english.md
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@ -7,18 +7,20 @@ videoId: N1ttsMmcVMM
---
## Description
<section id='description'>
More resources:
- <a href="https://notebooks.ai/rmotr-curriculum/freecodecamp-intro-to-numpy-6c285b74" target='_blank'>Notebook</a>
</section>
## Tests
<section id='tests'>
```yml
````yml
question:
text: |
What will the following code print out?:
What will the following code print out?
```py
a = np.arange(5)
@ -26,12 +28,23 @@ question:
print(a <= 3)
```
answers:
- "[False, False, False, False, True]"
- "[5]"
- "[0, 1, 2, 3]"
- "[True, True, True, True, False]"
- |
```python
[False, False, False, False, True]
```
- |
```python
[5]
```
- |
```python
[0, 1, 2, 3]
```
- |
```python
[True, True, True, True, False]
```
solution: 4
```
````
</section>

16
curriculum/challenges/english/08-data-analysis-with-python/data-analysis-with-python-course/numpy-introduction-a.english.md
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@ -7,23 +7,29 @@ videoId: P-JjV6GBCmk
---
## Description
<section id='description'>
More resources:
- <a href="https://notebooks.ai/rmotr-curriculum/freecodecamp-intro-to-numpy-6c285b74" target='_blank'>Notebook</a>
</section>
## Tests
<section id='tests'>
```yml
question:
text: "Why is Numpy an important, but unpopular Python library?"
text: |
Why is Numpy an important, but unpopular Python library?
answers:
- "Often you won't work directly with Numpy."
- "It's is extremely slow."
- "Working with Numpy is difficult."
- |
Often you won't work directly with Numpy.
- |
It's is extremely slow.
- |
Working with Numpy is difficult.
solution: 1
```
</section>

15
curriculum/challenges/english/08-data-analysis-with-python/data-analysis-with-python-course/numpy-introduction-b.english.md
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@ -7,12 +7,14 @@ videoId: YIqgrNLAZkA
---
## Description
<section id='description'>
More resources:
- <a href="https://notebooks.ai/rmotr-curriculum/freecodecamp-intro-to-numpy-6c285b74" target='_blank'>Notebook</a>
</section>
## Tests
<section id='tests'>
```yml
@ -20,12 +22,15 @@ question:
text: |
About how much memory does the integer `5` consume in plain Python?
answers:
- 32 bits
- 20 bytes
- 16 bytes
- 8 bits
- |
32 bits
- |
20 bytes
- |
16 bytes
- |
8 bits
solution: 2
```
</section>

17
curriculum/challenges/english/08-data-analysis-with-python/data-analysis-with-python-course/numpy-operations.english.md
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@ -20,7 +20,7 @@ More resources:
````yml
question:
text: |
What is the value of `a` after you run the following code?:
What is the value of `a` after you run the following code?
```py
a = np.arange(5)
@ -28,9 +28,18 @@ question:
```
answers:
- '[20, 21, 22, 24, 24]'
- '[0, 1, 2, 3, 4]'
- '[25, 26, 27, 28, 29]'
- |
```python
[20, 21, 22, 24, 24]
```
- |
```python
[0, 1, 2, 3, 4]
```
- |
```python
[25, 26, 27, 28, 29]
```
solution: 2
````

9
curriculum/challenges/english/08-data-analysis-with-python/data-analysis-with-python-course/pandas-condtitional-selection-and-modifying-dataframes.english.md
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@ -7,18 +7,20 @@ videoId: BFlH0fN5xRQ
---
## Description
<section id='description'>
More resources:
- <a href="https://notebooks.ai/rmotr-curriculum/freecodecamp-intro-to-pandas-902ae59b" target='_blank'>Notebook</a>
</section>
## Tests
<section id='tests'>
```yml
````yml
question:
text: |
What will the following code print out?:
What will the following code print out?
```py
import pandas as pd
@ -62,7 +64,6 @@ question:
Beau 6 7
```
solution: 2
```
````
</section>

9
curriculum/challenges/english/08-data-analysis-with-python/data-analysis-with-python-course/pandas-creating-columns.english.md
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@ -7,18 +7,20 @@ videoId: _sSo2XZoB3E
---
## Description
<section id='description'>
More resources:
- <a href="https://notebooks.ai/rmotr-curriculum/freecodecamp-intro-to-pandas-902ae59b" target='_blank'>Notebook</a>
</section>
## Tests
<section id='tests'>
```yml
````yml
question:
text: |
What code would add a "Certificates per month" column to the `certificates_earned` DataFrame like the one below?:
What code would add a "Certificates per month" column to the `certificates_earned` DataFrame like the one below?
```
Certificates Time (in months) Certificates per month
@ -49,7 +51,6 @@ question:
)
```
solution: 3
```
````
</section>

9
curriculum/challenges/english/08-data-analysis-with-python/data-analysis-with-python-course/pandas-dataframes.english.md
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@ -7,18 +7,20 @@ videoId: 7SgFBYXaiH0
---
## Description
<section id='description'>
More resources:
- <a href="https://notebooks.ai/rmotr-curriculum/freecodecamp-intro-to-pandas-902ae59b" target='_blank'>Notebook</a>
</section>
## Tests
<section id='tests'>
```yml
````yml
question:
text: |
What will the following code print out?:
What will the following code print out?
```py
import pandas as pd
@ -55,7 +57,6 @@ question:
Name: Ahmad, dtype: int64
```
solution: 3
```
````
</section>

9
curriculum/challenges/english/08-data-analysis-with-python/data-analysis-with-python-course/pandas-indexing-and-conditional-selection.english.md
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@ -7,18 +7,20 @@ videoId: -ZOrgV_aA9A
---
## Description
<section id='description'>
More resources:
- <a href="https://notebooks.ai/rmotr-curriculum/freecodecamp-intro-to-pandas-902ae59b" target='_blank'>Notebook</a>
</section>
## Tests
<section id='tests'>
```yml
````yml
question:
text: |
What will the following code print out?:
What will the following code print out?
```py
import pandas as pd
@ -54,7 +56,6 @@ question:
dtype: int64
```
solution: 3
```
````
</section>

9
curriculum/challenges/english/08-data-analysis-with-python/data-analysis-with-python-course/pandas-introduction.english.md
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@ -7,18 +7,20 @@ videoId: 0xACW-8cZU0
---
## Description
<section id='description'>
More resources:
- <a href="https://notebooks.ai/rmotr-curriculum/freecodecamp-intro-to-pandas-902ae59b" target='_blank'>Notebook</a>
</section>
## Tests
<section id='tests'>
```yml
````yml
question:
text: |
What will the following code print out?:
What will the following code print out?
```py
import pandas as pd
@ -57,7 +59,6 @@ question:
Name: certificates_earned dtype: int64
```
solution: 1
```
````
</section>

17
curriculum/challenges/english/08-data-analysis-with-python/data-analysis-with-python-course/parsing-html-and-saving-data.english.md
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@ -7,6 +7,7 @@ videoId: bJaqnTWQmb0
---
## Description
<section id='description'>
More resources:
- <a href="https://notebooks.ai/rmotr-curriculum/rdp-reading-csv-and-txt-files-fb829f46" target='_blank'>Reading CSVs Notebook</a>
@ -16,16 +17,22 @@ More resources:
</section>
## Tests
<section id='tests'>
```yml
question:
text: What Python library has the <code>.read_html()</code> method we can we use for parsing HTML documents and extracting tables?
text: |
What Python library has the `.read_html()` method we can we use for parsing HTML documents and extracting tables?
answers:
- 'BeautifierSoupy'
- 'WebReader'
- 'HTTP-master'
- 'Pandas'
- |
BeautifierSoupy
- |
WebReader
- |
HTTP-master
- |
Pandas
solution: 4
```

15
curriculum/challenges/english/08-data-analysis-with-python/data-analysis-with-python-course/python-functions-and-collections.english.md
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@ -7,23 +7,28 @@ videoId: NzpU17ZVlUw
---
## Description
<section id='description'>
More resources:
- <a href="https://notebooks.ai/rmotr-curriculum/python-under-10-minutes-15addcb2" target='_blank'>Notebook</a>
</section>
## Tests
<section id='tests'>
```yml
question:
text: What is the main difference between lists and tuples in Python?
text: |
What is the main difference between lists and tuples in Python?
answers:
- Tuples are immutable.
- Lists are ordered.
- Tuples are unordered.
- |
Tuples are immutable.
- |
Lists are ordered.
- |
Tuples are unordered.
solution: 1
```
</section>

17
curriculum/challenges/english/08-data-analysis-with-python/data-analysis-with-python-course/python-introduction.english.md
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@ -7,22 +7,29 @@ videoId: PrQV9JkLhb4
---
## Description
<section id='description'>
More resources:
- <a href="https://notebooks.ai/rmotr-curriculum/python-under-10-minutes-15addcb2" target='_blank'>Notebook</a>
</section>
## Tests
<section id='tests'>
```yml
question:
text: 'How do we define blocks of code in the body of functions in Python?'
text: |
How do we define blocks of code in the body of functions in Python?
answers:
- 'We use a set of curly braces, one on either side of each new block of our code.'
- 'We use indentation, usually right-aligned 4 spaces.'
- 'We do not denote blocks of code.'
- 'We could use curly braces or indentation to denote blocks of code.'
- |
We use a set of curly braces, one on either side of each new block of our code.
- |
We use indentation, usually right-aligned 4 spaces.
- |
We do not denote blocks of code.
- |
We could use curly braces or indentation to denote blocks of code.
solution: 2
```

34
curriculum/challenges/english/08-data-analysis-with-python/data-analysis-with-python-course/python-iteration-and-modules.english.md
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@ -7,23 +7,43 @@ videoId: XzosGWLafrY
---
## Description
<section id='description'>
More resources:
- <a href="https://notebooks.ai/rmotr-curriculum/python-under-10-minutes-15addcb2" target='_blank'>Notebook</a>
</section>
## Tests
<section id='tests'>
```yml
````yml
question:
text: How would you iterate over and print the keys and values of a dictionary named "user"?
text: |
How would you iterate over and print the keys and values of a dictionary named `user`?
answers:
- '<pre>for key in user.items():<br> print(key)</pre>'
- '<pre>for key, value in user.all():<br> print(key, value)<br> print(value)'
- '<pre>for key, value in user.items():<br> print(key, value)</pre>'
- '<pre>for key, value in user<br> print(key, value)</pre>'
- |
```python
for key in user.items():
print(key)
```
- |
```python
for key, value in user.all():
print(key, value)
print(value)
```
- |
```python
for key, value in user.items():
print(key, value)
```
- |
```python
for key, value in user
print(key, value)
```
solution: 3
```
````
</section>

34
curriculum/challenges/english/08-data-analysis-with-python/data-analysis-with-python-course/reading-data-csv-and-txt.english.md
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@ -7,6 +7,7 @@ videoId: ViGEv0zOzUk
---
## Description
<section id='description'>
More resources:
- <a href="https://notebooks.ai/rmotr-curriculum/rdp-reading-csv-and-txt-files-fb829f46" target='_blank'>Reading CSVs Notebook</a>
@ -16,18 +17,35 @@ More resources:
</section>
## Tests
<section id='tests'>
```yml
````yml
question:
text: 'How would you import the CSV file "data.csv" and store it in a DataFrame using the Pandas module?'
text: |
How would you import the CSV file `data.csv` and store it in a DataFrame using the Pandas module?
answers:
- '<pre>import pandas as pd<br>df = pd.csv("data.csv")</pre>'
- '<pre>import pandas as pd<br>df = pd.read_csv("data.csv")</pre>'
- '<pre>import pandas as pd<br>pd.read_csv("data.csv")</pre>'
- '<pre>import pandas as pd<br>df = pd.csv_reader("data.csv")</pre>'
- |
```python
import pandas as pd
df = pd.csv("data.csv")
```
- |
```python
import pandas as pd
df = pd.read_csv("data.csv")
```
- |
```python
import pandas as pd
pd.read_csv("data.csv")
```
- |
```python
import pandas as pd
df = pd.csv_reader("data.csv")
```
solution: 2
```
````
</section>

14
curriculum/challenges/english/08-data-analysis-with-python/data-analysis-with-python-course/reading-data-from-databases.english.md
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@ -7,6 +7,7 @@ videoId: MtgXS1MofRw
---
## Description
<section id='description'>
More resources:
- <a href="https://notebooks.ai/rmotr-curriculum/rdp-reading-csv-and-txt-files-fb829f46" target='_blank'>Reading CSVs Notebook</a>
@ -16,15 +17,20 @@ More resources:
</section>
## Tests
<section id='tests'>
```yml
question:
text: What method does a <code>Cursor</code> instance have and what does it allow?
text: |
What method does a `Cursor` instance have and what does it allow?
answers:
- The <code>Cursor</code> instance has a <code>.run()</code> method which allows you to run SQL queries.
- The <code>Cursor</code> instance has a <code>.select()</code> method which allows you to select records.
- The <code>Cursor</code> instance has an <code>.execute()</code> method which will receive SQL parameters to run against the database.
- |
The `Cursor` instance has a `.run()` method which allows you to run SQL queries.
- |
The `Cursor` instance has a `.select()` method which allows you to select records.
- |
The `Cursor` instance has an `.execute()` method which will receive SQL parameters to run against the database.
solution: 3
```

8
curriculum/challenges/english/08-data-analysis-with-python/data-analysis-with-python-course/reading-data-introduction.english.md
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@ -7,6 +7,7 @@ videoId: cDnt02BcHng
---
## Description
<section id='description'>
More resources:
- <a href="https://notebooks.ai/rmotr-curriculum/rdp-reading-csv-and-txt-files-fb829f46" target='_blank'>Reading CSVs Notebook</a>
@ -16,9 +17,10 @@ More resources:
</section>
## Tests
<section id='tests'>
```yml
````yml
question:
text: |
Given a file named `certificates.csv` with these contents:
@ -58,14 +60,12 @@ question:
C: `certs_num`
- |
A: `'certificates'`
B: `'$'`
C: `certs_num`
solution: 2
```
````
</section>

25
curriculum/challenges/english/08-data-analysis-with-python/numpy/accessing-and-changing-elements,-rows,-columns.english.md
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@ -7,16 +7,18 @@ videoId: v-7Y7koJ_N0
---
## Description
<section id='description'>
</section>
## Tests
<section id='tests'>
```yml
````yml
question:
text: |
What code would change the values in the 3rd column of both of the following Numpy arrays to 20?:
What code would change the values in the 3rd column of both of the following Numpy arrays to 20?
```py
a = np.array([[1, 2, 3, 4, 5], [6, 7, 8, 9, 10]])
@ -27,15 +29,22 @@ question:
```
answers:
- |
`a[:, 3] = 20`
```python
a[:, 3] = 20
```
- |
`a[2, :] = 20`
```python
a[2, :] = 20
```
- |
`a[:, 2] = 20`
```python
a[:, 2] = 20
```
- |
`a[1, 2] = 20`
```python
a[1, 2] = 20
```
solution: 3
```
````
</section>

34
curriculum/challenges/english/08-data-analysis-with-python/numpy/basics-of-numpy.english.md
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@ -7,21 +7,41 @@ videoId: f9QrZrKQMLI
---
## Description
<section id='description'>
</section>
## Tests
<section id='tests'>
```yml
````yml
question:
text: 'What will the following code print?:<pre>b = np.array([[1.0,2.0,3.0],[3.0,4.0,5.0]])<br>print(b)</pre>'
text: |
What will the following code print?
```python
b = np.array([[1.0,2.0,3.0],[3.0,4.0,5.0]])
print(b)
```
answers:
- '<pre>[[1.0 2.0 3.0]<br>[3.0 4.0 5.0]]<pre>'
- '<pre>[[1. 2. 3.]<br>[3. 4. 5.]]<pre>'
- '<pre>[[1. 3.]<br>[2. 4.]<br>[3. 5.]<pre>'
- |
```python
[[1.0 2.0 3.0]
[3.0 4.0 5.0]]
```
- |
```python
[[1. 2. 3.]
[3. 4. 5.]]
```
- |
```python
[[1. 3.]
[2. 4.]
[3. 5.]
```
solution: 2
```
````
</section>

21
curriculum/challenges/english/08-data-analysis-with-python/numpy/copying-arrays-warning.english.md
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@ -7,16 +7,18 @@ videoId: iIoQ0_L0GvA
---
## Description
<section id='description'>
</section>
## Tests
<section id='tests'>
```yml
````yml
question:
text: |
What is the value of `a` after running the following code?:
What is the value of `a` after running the following code?
```py
import numpy as np
@ -28,13 +30,18 @@ question:
answers:
- |
`[1 2 3 4 5]`
```python
[1 2 3 4 5]
```
- |
`[1 2 20 4 5]`
```python
[1 2 20 4 5]
```
- |
`[1 20 3 4 5]`
```python
[1 20 3 4 5]
```
solution: 2
```
````
</section>

11
curriculum/challenges/english/08-data-analysis-with-python/numpy/initialize-array-problem.english.md
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@ -7,18 +7,20 @@ videoId: 0jGfH8BPfOk
---
## Description
<section id='description'>
</section>
## Tests
<section id='tests'>
```yml
````yml
question:
text: |
What is another way to produce the following array?:
What is another way to produce the following array?
```
```py
[[1. 1. 1. 1. 1.]
[1. 0. 0. 0. 1.]
[1. 0. 9. 0. 1.]
@ -55,7 +57,6 @@ question:
output[4:1, 4:1] = z
```
solution: 1
```
````
</section>

15
curriculum/challenges/english/08-data-analysis-with-python/numpy/initializing-different-arrays.english.md
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@ -7,16 +7,18 @@ videoId: CEykdsKT4U4
---
## Description
<section id='description'>
</section>
## Tests
<section id='tests'>
```yml
````yml
question:
text: |
What will the following code print?:
What will the following code print?
```py
a = np.array([[1, 2, 3, 4, 5], [6, 7, 8, 9, 10]])
@ -25,21 +27,20 @@ question:
```
answers:
- |
```
```py
[[100 100 100 100 100]]
```
- |
```
```py
[[100 100 100 100 100]
[100 100 100 100 100]]
```
- |
```
```py
[[ 1 2 3 4 5]
[ 6 7 20 9 10]]
```
solution: 2
```
````
</section>

15
curriculum/challenges/english/08-data-analysis-with-python/numpy/loading-data-and-advanced-indexing.english.md
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@ -7,13 +7,15 @@ videoId: tUdBZ7pF8Jg
---
## Description
<section id='description'>
</section>
## Tests
<section id='tests'>
```yml
````yml
question:
text: |
Given a file named `data.txt` with these contents:
@ -23,7 +25,7 @@ question:
15,88,5,75,22
```
What code would produce the following array?:
What code would produce the following array?
```py
[29. 32. 45. 15. 5. 22.]
@ -31,28 +33,27 @@ question:
answers:
- |
```
```py
filedata = np.genfromtxt('data.txt', delimiter=',')
output = np.any(filedata < 50)
print(output)
```
- |
```
```py
filedata = np.genfromtxt('data.txt', delimiter=',')
output = np.all(filedata < 50, axis=1)
print(output)
```
- |
```
```py
filedata = np.genfromtxt('data.txt', delimiter=',')
output = filedata[filedata < 50]
print(output)
```
solution: 3
```
````
</section>

29
curriculum/challenges/english/08-data-analysis-with-python/numpy/mathematics.english.md
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@ -7,16 +7,18 @@ videoId: 7txegvyhtVk
---
## Description
<section id='description'>
</section>
## Tests
<section id='tests'>
```yml
````yml
question:
text: |
What is the value of `b` after running the following code?:
What is the value of `b` after running the following code?
```py
import numpy as np
@ -26,12 +28,23 @@ question:
```
answers:
- '10'
- '7'
- '5'
- '15'
- |
```py
10
```
- |
```py
7
```
- |
```py
5
```
- |
```py
15
```
solution: 4
```
````
</section>

11
curriculum/challenges/english/08-data-analysis-with-python/numpy/reorganizing-arrays.english.md
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@ -7,18 +7,20 @@ videoId: VNWAQbEM-C8
---
## Description
<section id='description'>
</section>
## Tests
<section id='tests'>
```yml
````yml
question:
text: |
What code would produce the following array?:
What code would produce the following array?
```
```py
[[1. 1.]
[1. 1.]
[1. 1.]
@ -44,7 +46,6 @@ question:
print(b)
```
solution: 1
```
````
</section>

19
curriculum/challenges/english/08-data-analysis-with-python/numpy/what-is-numpy.english.md
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@ -7,22 +7,29 @@ videoId: 5Nwfs5Ej85Q
---
## Description
<section id='description'>
</section>
## Tests
<section id='tests'>
```yml
question:
text: 'Why are Numpy arrays faster than regular Python lists?:'
text: |
Why are Numpy arrays faster than regular Python lists?
answers:
- Numpy does not perform type checking while iterating through objects.
- Numpy uses fixed types.
- Numpy uses contiguous memory.
- All of the above.
- |
Numpy does not perform type checking while iterating through objects.
- |
Numpy uses fixed types.
- |
Numpy uses contiguous memory.
- |
All of the above.
solution: 4
```
</section>

6
curriculum/challenges/english/09-information-security/python-for-penetration-testing/developing-a-port-scanner.english.md
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@ -7,10 +7,12 @@ videoId: z_qkqZS7KZ4
---
## Description
<section id='description'>
</section>
## Tests
<section id='tests'>
```yml
@ -19,7 +21,8 @@ question:
What is the main difference between the `.connect()` and `.connect_ex()` methods?
answers:
- There is no difference between the two methods.
- |
There is no difference between the two methods.
- |
If there is an error or if no host is found, `.connect()` returns an error code while `.connect_ex()` raises an exception.
- |
@ -28,4 +31,3 @@ question:
```
</section>

12
curriculum/challenges/english/09-information-security/python-for-penetration-testing/introduction-and-setup.english.md
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@ -7,10 +7,12 @@ videoId: XeQ7ZKtb998
---
## Description
<section id='description'>
</section>
## Tests
<section id='tests'>
```yml
@ -19,11 +21,13 @@ question:
What code editor and extension does the instructor recommend for developing penetration testing tools in Python?
answers:
- Atom and the atom-python-run extension.
- VSCode and Microsoft's Python extension.
- Sublime Text and the Anaconda package.
- |
Atom and the atom-python-run extension.
- |
VSCode and Microsoft's Python extension.
- |
Sublime Text and the Anaconda package.
solution: 2
```
</section>

18
curriculum/challenges/english/11-machine-learning-with-python/how-neural-networks-work/deep-learning-demystified.english.md
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@ -7,23 +7,29 @@ videoId: bejQ-W9BGJg
---
## Description
<section id='description'>
</section>
## Tests
<section id='tests'>
```yml
question:
text: How should you assign weights to input neurons before training your network for the first time?
text: |
How should you assign weights to input neurons before training your network for the first time?
answers:
- From smallest to largest.
- Completely randomly.
- Alphabetically.
- None of the above.
- |
From smallest to largest.
- |
Completely randomly.
- |
Alphabetically.
- |
None of the above.
solution: 2
```
</section>

15
curriculum/challenges/english/11-machine-learning-with-python/how-neural-networks-work/how-convolutional-neural-networks-work.english.md
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@ -7,22 +7,27 @@ videoId: Y5M7KH4A4n4
---
## Description
<section id='description'>
</section>
## Tests
<section id='tests'>
```yml
question:
text: When are Convolutional Neural Networks not useful?
text: |
When are Convolutional Neural Networks not useful?
answers:
- If your data can't be made to look like an image, or if you can rearrange elements of your data and it's still just as useful.
- If your data is made up of different 2D or 3D images.
- If your data is text or sound based.
- |
If your data can't be made to look like an image, or if you can rearrange elements of your data and it's still just as useful.
- |
If your data is made up of different 2D or 3D images.
- |
If your data is text or sound based.
solution: 1
```
</section>

15
curriculum/challenges/english/11-machine-learning-with-python/how-neural-networks-work/how-deep-neural-networks-work.english.md
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@ -7,22 +7,27 @@ videoId: zvalnHWGtx4
---
## Description
<section id='description'>
</section>
## Tests
<section id='tests'>
```yml
question:
text: Why is it better to calculate the gradient (slope) directly rather than numerically?
text: |
Why is it better to calculate the gradient (slope) directly rather than numerically?
answers:
- It is computationally expensive to go back through the entire neural network and adjust the weights for each layer of the neural network.
- It is more accurate.
- There is no difference between the two methods.
- |
It is computationally expensive to go back through the entire neural network and adjust the weights for each layer of the neural network.
- |
It is more accurate.
- |
There is no difference between the two methods.
solution: 1
```
</section>

12
curriculum/challenges/english/11-machine-learning-with-python/how-neural-networks-work/recurrent-neural-networks-rnn-and-long-short-term-memory-lstm.english.md
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@ -7,10 +7,12 @@ videoId: UVimlsy9eW0
---
## Description
<section id='description'>
</section>
## Tests
<section id='tests'>
```yml
@ -19,11 +21,13 @@ question:
What are the main neural network components that make up a Long Short Term Memory network?
answers:
- New information and prediction.
- Prediction, collected possibilities, and selection.
- Prediction, ignoring, forgetting, and selection.
- |
New information and prediction.
- |
Prediction, collected possibilities, and selection.
- |
Prediction, ignoring, forgetting, and selection.
solution: 3
```
</section>

12
curriculum/challenges/english/11-machine-learning-with-python/tensorflow/conclusion.english.md
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@ -7,10 +7,12 @@ videoId: LMNub5frQi4
---
## Description
<section id='description'>
</section>
## Tests
<section id='tests'>
```yml
@ -18,11 +20,13 @@ question:
text: |
Most people that are experts in AI or machine learning usually...:
answers:
- have one specialization.
- have many specializations.
- have a deep understanding of many different frameworks.
- |
have one specialization.
- |
have many specializations.
- |
have a deep understanding of many different frameworks.
solution: 1
```
</section>

15
curriculum/challenges/english/11-machine-learning-with-python/tensorflow/convolutional-neural-networks-evaluating-the-model.english.md
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@ -7,21 +7,26 @@ videoId: eCATNvwraXg
---
## Description
<section id='description'>
</section>
## Tests
<section id='tests'>
```yml
question:
text: What is **not** a good way to increase the accuracy of a convolutional neural network?
text: |
What is **not** a good way to increase the accuracy of a convolutional neural network?
answers:
- Augmenting the data you already have.
- Using a pre-trained model.
- Using your test data to retrain the model.
- |
Augmenting the data you already have.
- |
Using a pre-trained model.
- |
Using your test data to retrain the model.
solution: 3
```
</section>

15
curriculum/challenges/english/11-machine-learning-with-python/tensorflow/convolutional-neural-networks-the-convolutional-layer.english.md
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@ -7,21 +7,26 @@ videoId: LrdmcQpTyLw
---
## Description
<section id='description'>
</section>
## Tests
<section id='tests'>
```yml
question:
text: What are the three main properties of each convolutional layer?
text: |
What are the three main properties of each convolutional layer?
answers:
- Input size, the number of filters, and the sample size of the filters.
- Input size, input dimensions, and the color values of the input.
- Input size, input padding, and stride.
- |
Input size, the number of filters, and the sample size of the filters.
- |
Input size, input dimensions, and the color values of the input.
- |
Input size, input padding, and stride.
solution: 1
```
</section>

12
curriculum/challenges/english/11-machine-learning-with-python/tensorflow/convolutional-neural-networks.english.md
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@ -7,10 +7,12 @@ videoId: _1kTP7uoU9E
---
## Description
<section id='description'>
</section>
## Tests
<section id='tests'>
```yml
@ -18,11 +20,13 @@ question:
text: |
Dense neural networks analyze input on a global scale and recognize patterns in specific areas. Convolutional neural networks...:
answers:
- also analyze input globally and extract features from specific areas.
- do not work well for image classification or object detection.
- scan through the entire input a little at a time and learn local patterns.
- |
also analyze input globally and extract features from specific areas.
- |
do not work well for image classification or object detection.
- |
scan through the entire input a little at a time and learn local patterns.
solution: 3
```
</section>

6
curriculum/challenges/english/11-machine-learning-with-python/tensorflow/core-learning-algorithms-building-the-model.english.md
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@ -7,15 +7,18 @@ videoId: 5wHw8BTd2ZQ
---
## Description
<section id='description'>
</section>
## Tests
<section id='tests'>
```yml
question:
text: What kind of estimator/model does TensorFlow recommend using for classification?
text: |
What kind of estimator/model does TensorFlow recommend using for classification?
answers:
- |
`LinearClassifier`
@ -27,4 +30,3 @@ question:
```
</section>

15
curriculum/challenges/english/11-machine-learning-with-python/tensorflow/core-learning-algorithms-classification.english.md
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@ -7,21 +7,26 @@ videoId: qFF7ZQNvK9E
---
## Description
<section id='description'>
</section>
## Tests
<section id='tests'>
```yml
question:
text: What is classification?
text: |
What is classification?
answers:
- The process of separating data points into different classes.
- Predicting a numeric value or forecast based on independent and dependent variables.
- None of the above.
- |
The process of separating data points into different classes.
- |
Predicting a numeric value or forecast based on independent and dependent variables.
- |
None of the above.
solution: 1
```
</section>

21
curriculum/challenges/english/11-machine-learning-with-python/tensorflow/core-learning-algorithms-clustering.english.md
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@ -7,23 +7,30 @@ videoId: 8sqIaHc9Cz4
---
## Description
<section id='description'>
</section>
## Tests
<section id='tests'>
```yml
question:
text: Which of the following steps is **not** part of the K-Means algorithm?
text: |
Which of the following steps is **not** part of the K-Means algorithm?
answers:
- Randomly pick K points to place K centeroids.
- Assign each K point to the closest K centeroid.
- Move each K centeroid into the middle of all of their data points.
- Shuffle the K points so they're redistributed randomly.
- Reassign each K point to the closest K centeroid.
- |
Randomly pick K points to place K centeroids.
- |
Assign each K point to the closest K centeroid.
- |
Move each K centeroid into the middle of all of their data points.
- |
Shuffle the K points so they're redistributed randomly.
- |
Reassign each K point to the closest K centeroid.
solution: 4
```
</section>

15
curriculum/challenges/english/11-machine-learning-with-python/tensorflow/core-learning-algorithms-hidden-markov-models.english.md
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@ -7,21 +7,26 @@ videoId: IZg24y4wEPY
---
## Description
<section id='description'>
</section>
## Tests
<section id='tests'>
```yml
question:
text: What makes a Hidden Markov model different than linear regression or classification?
text: |
What makes a Hidden Markov model different than linear regression or classification?
answers:
- It uses probability distributions to predict future events or states.
- It analyzes the relationship between independent and dependent variables to make predictions.
- It separates data points into separate categories.
- |
It uses probability distributions to predict future events or states.
- |
It analyzes the relationship between independent and dependent variables to make predictions.
- |
It separates data points into separate categories.
solution: 1
```
</section>

15
curriculum/challenges/english/11-machine-learning-with-python/tensorflow/core-learning-algorithms-the-training-process.english.md
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@ -7,21 +7,26 @@ videoId: _cEwvqVoBhI
---
## Description
<section id='description'>
</section>
## Tests
<section id='tests'>
```yml
question:
text: What are epochs?
text: |
What are epochs?
answers:
- The number of times the model will see the same data.
- A type of graph.
- The number of elements you feed to the model at once.
- |
The number of times the model will see the same data.
- |
A type of graph.
- |
The number of elements you feed to the model at once.
solution: 1
```
</section>

15
curriculum/challenges/english/11-machine-learning-with-python/tensorflow/core-learning-algorithms-training-and-testing-data.english.md
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@ -7,21 +7,26 @@ videoId: wz9J1slsi7I
---
## Description
<section id='description'>
</section>
## Tests
<section id='tests'>
```yml
question:
text: What is categorical data?
text: |
What is categorical data?
answers:
- Another term for one-hot encoding.
- Any data that is not numeric.
- Any data that is represented numerically.
- |
Another term for one-hot encoding.
- |
Any data that is not numeric.
- |
Any data that is represented numerically.
solution: 2
```
</section>

6
curriculum/challenges/english/11-machine-learning-with-python/tensorflow/core-learning-algorithms-using-probabilities-to-make-predictions.english.md
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@ -7,15 +7,18 @@ videoId: fYAYvLUawnc
---
## Description
<section id='description'>
</section>
## Tests
<section id='tests'>
```yml
question:
text: What TensorFlow module should you import to implement `.HiddenMarkovModel()`?
text: |
What TensorFlow module should you import to implement `.HiddenMarkovModel()`?
answers:
- |
`tensorflow.keras`
@ -27,4 +30,3 @@ question:
```
</section>

12
curriculum/challenges/english/11-machine-learning-with-python/tensorflow/core-learning-algorithms-working-with-data.english.md
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---
## Description
<section id='description'>
</section>
## Tests
<section id='tests'>
```yml
@ -18,11 +20,13 @@ question:
text: |
What does the pandas `.head()` function do?
answers:
- Returns the number of entries in a data frame.
- Returns the number of columns in a data frame.
- By default, shows the first five rows or entries in a data frame.
- |
Returns the number of entries in a data frame.
- |
Returns the number of columns in a data frame.
- |
By default, shows the first five rows or entries in a data frame.
solution: 3
```
</section>

15
curriculum/challenges/english/11-machine-learning-with-python/tensorflow/core-learning-algorithms.english.md
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---
## Description
<section id='description'>
</section>
## Tests
<section id='tests'>
```yml
@ -20,12 +22,15 @@ question:
You have the average temperature in the month of March for the last 100 years. Using this data, you want to predict the average temperature in the month of March 5 years from now.
answers:
- Multiple regression
- Correlation
- Decision tree
- Linear regression
- |
Multiple regression
- |
Correlation
- |
Decision tree
- |
Linear regression
solution: 4
```
</section>

14
curriculum/challenges/english/11-machine-learning-with-python/tensorflow/introduction-machine-learning-fundamentals.english.md
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@ -1,16 +1,18 @@
---
id: 5e8f2f13c4cdbe86b5c72d87
title: "Introduction: Machine Learning Fundamentals"
title: 'Introduction: Machine Learning Fundamentals'
challengeType: 11
isHidden: false
videoId: KwL1qTR5MT8
---
## Description
<section id='description'>
</section>
## Tests
<section id='tests'>
```yml
@ -18,11 +20,13 @@ question:
text: |
Which statement below is **false**?
answers:
- Neural networks are modeled after the way the human brain works.
- Computer programs that play tic-tac-toe or chess against human players are examples of simple artificial intelligence.
- Machine learning is a subset of artificial intelligence.
- |
Neural networks are modeled after the way the human brain works.
- |
Computer programs that play tic-tac-toe or chess against human players are examples of simple artificial intelligence.
- |
Machine learning is a subset of artificial intelligence.
solution: 1
```
</section>

21
curriculum/challenges/english/11-machine-learning-with-python/tensorflow/introduction-to-tensorflow.english.md
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---
## Description
<section id='description'>
</section>
## Tests
<section id='tests'>
```yml
question:
text: Which of the following is **not** a type of tensor?
text: |
Which of the following is **not** a type of tensor?
answers:
- Variable
- Flowing
- Placeholder
- SparseTensor
- Constant
- |
Variable
- |
Flowing
- |
Placeholder
- |
SparseTensor
- |
Constant
solution: 2
```
</section>

12
curriculum/challenges/english/11-machine-learning-with-python/tensorflow/natural-language-processing-with-rnns-making-predictions.english.md
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@ -7,10 +7,12 @@ videoId: WO1hINnBj20
---
## Description
<section id='description'>
</section>
## Tests
<section id='tests'>
```yml
@ -18,11 +20,13 @@ question:
text: |
Before you make a prediction with your own review, you should...:
answers:
- decode the training dataset and compare the results to the test data.
- use the encodings from the training dataset to encode your review.
- assign random values between 0 and the maximum number of vocabulary in your dataset to each word in your review.
- |
decode the training dataset and compare the results to the test data.
- |
use the encodings from the training dataset to encode your review.
- |
assign random values between 0 and the maximum number of vocabulary in your dataset to each word in your review.
solution: 2
```
</section>

12
curriculum/challenges/english/11-machine-learning-with-python/tensorflow/natural-language-processing-with-rnns-part-2.english.md
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@ -7,10 +7,12 @@ videoId: mUU9YXOFbZg
---
## Description
<section id='description'>
</section>
## Tests
<section id='tests'>
```yml
@ -18,11 +20,13 @@ question:
text: |
Word embeddings are...:
answers:
- an unordered group of encoded words that describes the frequency of words in a given document.
- a group of encoded words that preserves the original order of the words in a given document.
- a vectorized representation of words in a given document that places words with similar meanings near each other.
- |
an unordered group of encoded words that describes the frequency of words in a given document.
- |
a group of encoded words that preserves the original order of the words in a given document.
- |
a vectorized representation of words in a given document that places words with similar meanings near each other.
solution: 3
```
</section>

6
curriculum/challenges/english/11-machine-learning-with-python/tensorflow/natural-language-processing-with-rnns-recurring-neural-networks.english.md
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@ -7,15 +7,18 @@ videoId: bX5681NPOcA
---
## Description
<section id='description'>
</section>
## Tests
<section id='tests'>
```yml
question:
text: What is true about Recurrent Neural Networks?
text: |
What is true about Recurrent Neural Networks?
answers:
- |
1: They are a type of feed-forward neural network.
@ -29,4 +32,3 @@ question:
```
</section>

12
curriculum/challenges/english/11-machine-learning-with-python/tensorflow/natural-language-processing-with-rnns.english.md
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@ -7,10 +7,12 @@ videoId: ZyCaF5S-lKg
---
## Description
<section id='description'>
</section>
## Tests
<section id='tests'>
```yml
@ -18,11 +20,13 @@ question:
text: |
Natural Language Processing is a branch of artificial intelligence that...:
answers:
- deals with how computers understand and process natural/human languages.
- translates image data into natural/human languages.
- is focused on translating computer languages into natural/human languages.
- |
deals with how computers understand and process natural/human languages.
- |
translates image data into natural/human languages.
- |
is focused on translating computer languages into natural/human languages.
solution: 1
```
</section>

15
curriculum/challenges/english/11-machine-learning-with-python/tensorflow/neural-networks-activation-functions.english.md
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@ -7,21 +7,26 @@ videoId: S45tqW6BqRs
---
## Description
<section id='description'>
</section>
## Tests
<section id='tests'>
```yml
question:
text: Which activation function switches values between -1 and 1?
text: |
Which activation function switches values between -1 and 1?
answers:
- ReLU (Rectified Linear Unit)
- Tanh (Hyperbolic Tangent)
- Sigmoid
- |
ReLU (Rectified Linear Unit)
- |
Tanh (Hyperbolic Tangent)
- |
Sigmoid
solution: 2
```
</section>

15
curriculum/challenges/english/11-machine-learning-with-python/tensorflow/neural-networks-optimizers.english.md
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---
## Description
<section id='description'>
</section>
## Tests
<section id='tests'>
```yml
question:
text: What is an optimizer function?
text: |
What is an optimizer function?
answers:
- A function that increases the accuracy of a model's predictions.
- A function that implements the gradient descent and backpropagation algorithms for you.
- A function that reduces the time a model needs to train.
- |
A function that increases the accuracy of a model's predictions.
- |
A function that implements the gradient descent and backpropagation algorithms for you.
- |
A function that reduces the time a model needs to train.
solution: 2
```
</section>

12
curriculum/challenges/english/11-machine-learning-with-python/tensorflow/neural-networks-with-tensorflow.english.md
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@ -7,10 +7,12 @@ videoId: uisdfrNrZW4
---
## Description
<section id='description'>
</section>
## Tests
<section id='tests'>
```yml
@ -18,11 +20,13 @@ question:
text: |
A densely connected neural network is one in which...:
answers:
- all the neurons in the current layer are connected to one neuron in the previous layer.
- all the neurons in each layer are connected randomly.
- all the neurons in the current layer are connected to every neuron in the previous layer.
- |
all the neurons in the current layer are connected to one neuron in the previous layer.
- |
all the neurons in each layer are connected randomly.
- |
all the neurons in the current layer are connected to every neuron in the previous layer.
solution: 3
```
</section>

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curriculum/challenges/english/11-machine-learning-with-python/tensorflow/reinforcement-learning-with-q-learning-part-2.english.md
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@ -7,20 +7,24 @@ videoId: DX7hJuaUZ7o
---
## Description
<section id='description'>
</section>
## Tests
<section id='tests'>
```yml
question:
text: What can happen if the agent does not have a good balance of taking random actions and using learned actions?
text: |
What can happen if the agent does not have a good balance of taking random actions and using learned actions?
answers:
- The agent will always try to minimize its reward for the current state/action, leading to local minima.
- The agent will always try to maximize its reward for the current state/action, leading to local maxima.
- |
The agent will always try to minimize its reward for the current state/action, leading to local minima.
- |
The agent will always try to maximize its reward for the current state/action, leading to local maxima.
solution: 2
```
</section>

15
curriculum/challenges/english/11-machine-learning-with-python/tensorflow/reinforcement-learning-with-q-learning.english.md
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@ -7,21 +7,26 @@ videoId: Cf7DSU0gVb4
---
## Description
<section id='description'>
</section>
## Tests
<section id='tests'>
```yml
question:
text: The key components of reinforcement learning are...
text: |
The key components of reinforcement learning are...
answers:
- environment, representative, state, reaction, and reward.
- environment, agent, state, action, and reward.
- habitat, agent, state, action, and punishment.
- |
environment, representative, state, reaction, and reward.
- |
environment, agent, state, action, and reward.
- |
habitat, agent, state, action, and punishment.
solution: 2
```
</section>