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Added bits cheat sheet.

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John Washam
2016-07-24 16:42:28 -07:00
parent 48fe3d9a2a
commit 9f1a81951a
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README.md
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@ -48,7 +48,7 @@ More about Github flavored markdown: https://guides.github.com/features/masterin
## Get in a Googley Mood ## Get in a Googley Mood
Print out a "[future Googler](https://github.com/jwasham/project-9894/blob/master/future-googler.pdf)" sign (or two) and keep your eyes on the prize. Print out a "[future Googler](https://github.com/jwasham/google-interview-university/blob/master/extras/future-googler.pdf)" sign (or two) and keep your eyes on the prize.
## Follow me ## Follow me
@ -1088,11 +1088,15 @@ Some of mine (I already may know answer to but want their opinion or team perspe
- [ ] Machine Learning: - [ ] Machine Learning:
- Why ML? - Why ML?
- [x] https://backchannel.com/how-google-is-remaking-itself-as-a-machine-learning-first-company-ada63defcb70 - [x] https://backchannel.com/how-google-is-remaking-itself-as-a-machine-learning-first-company-ada63defcb70
- [ ] Google Developers' Machine Learning Recipes (Scikit Learn & Tensorflow):
- https://www.youtube.com/playlist?list=PLOU2XLYxmsIIuiBfYad6rFYQU_jL2ryal
- [x] great course (Stanford): https://www.coursera.org/learn/machine-learning - [x] great course (Stanford): https://www.coursera.org/learn/machine-learning
- [ ] Google course on Udacity: https://www.udacity.com/course/deep-learning--ud730 - [ ] Google's Deep Learning Nanodegree: https://www.udacity.com/course/deep-learning--ud730
- https://www.youtube.com/watch?list=PLOU2XLYxmsIIuiBfYad6rFYQU_jL2ryal&v=cSKfRcEDGUs&app=desktop - [ ] Google/Kaggle Machine Learning Engineer Nanodegree: https://www.udacity.com/course/machine-learning-engineer-nanodegree-by-google--nd009
- http://www.analyticsvidhya.com/blog/2016/04/neural-networks-python-theano/ - [ ] Self-Driving Car Engineer Nanodegree: https://www.udacity.com/course/self-driving-car-engineer-nanodegree--nd013
- http://www.dataschool.io/ - [ ] Metis Online Course ($99 for 2 months): http://www.thisismetis.com/explore-data-science
- [ ] Practical Guide to implementing Neural Networks in Python (using Theano): http://www.analyticsvidhya.com/blog/2016/04/neural-networks-python-theano/
- Data School: http://www.dataschool.io/
- [ ] Vector calculus - [ ] Vector calculus
- [ ] Parallel Programming: - [ ] Parallel Programming:

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extras/bits-cheat-cheet.pdf Normal file
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extras/bits.php Normal file
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<html>
<style>
body {
font-family: courier, fixed, sans-serif;
}
h1 {
font-size: 1.25em;
}
table, td {
border: 1px #cccccc solid;
}
table {
border-collapse: collapse;
}
td, th {
padding: 0.3em 1em;
font-size: 0.85em;
}
tbody tr:nth-child(odd) {
background-color: #f3f3f3; /* zebra stripes */
}
</style>
<body>
<h1>Bits Cheat Sheet</h1>
<table>
<thead>
<tr>
<th>&nbsp;</th>
<th>2<sup>n</sup></th>
<th>Bits</th>
<th>Max unsigned int</th>
<th>Min signed int</th>
<th>Max signed int</th>
</tr>
</thead>
<tbody>
<? foreach(range(1, 32) as $b): ?>
<tr>
<td>2<sup><?=$b ?></sup></td>
<td><?=number_format(pow(2, $b)) ?></td>
<td><?=$b ?></td>
<td><?=number_format(pow(2, $b) - 1) ?></td>
<td><? $num = pow(2, $b) / 2 * -1 ?><?=number_format($num) ?></td>
<td><? $num = pow(2, $b) / 2 - 1 ?><?=number_format($num) ?></td>
</tr>
<? endforeach; ?>
</tbody>
</table>
</body>
</html>

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future-googler.pdf → extras/future-googler.pdf
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