chore: enable python curriculum (#39118)
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id: 5e8f2f13c4cdbe86b5c72da6
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title: Conclusion
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challengeType: 11
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isHidden: true
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isHidden: false
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videoId: LMNub5frQi4
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id: 5e8f2f13c4cdbe86b5c72d99
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title: 'Convolutional Neural Networks: Evaluating the Model'
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challengeType: 11
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isHidden: true
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isHidden: false
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videoId: eCATNvwraXg
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id: 5e8f2f13c4cdbe86b5c72d9a
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title: 'Convolutional Neural Networks: Picking a Pretrained Model'
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challengeType: 11
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isHidden: true
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isHidden: false
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videoId: h1XUt1AgIOI
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---
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id: 5e8f2f13c4cdbe86b5c72d97
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title: 'Convolutional Neural Networks: The Convolutional Layer'
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challengeType: 11
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isHidden: true
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isHidden: false
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videoId: LrdmcQpTyLw
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---
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id: 5e8f2f13c4cdbe86b5c72d96
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title: Convolutional Neural Networks
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challengeType: 11
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isHidden: true
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isHidden: false
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videoId: _1kTP7uoU9E
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---
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id: 5e8f2f13c4cdbe86b5c72d8e
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title: 'Core Learning Algorithms: Building the Model'
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challengeType: 11
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isHidden: true
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isHidden: false
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videoId: 5wHw8BTd2ZQ
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---
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id: 5e8f2f13c4cdbe86b5c72d8d
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title: 'Core Learning Algorithms: Classification'
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challengeType: 11
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isHidden: true
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isHidden: false
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videoId: qFF7ZQNvK9E
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---
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id: 5e8f2f13c4cdbe86b5c72d8f
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title: 'Core Learning Algorithms: Clustering'
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challengeType: 11
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isHidden: true
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isHidden: false
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videoId: 8sqIaHc9Cz4
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---
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id: 5e8f2f13c4cdbe86b5c72d90
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title: 'Core Learning Algorithms: Hidden Markov Models'
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challengeType: 11
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isHidden: true
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isHidden: false
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videoId: IZg24y4wEPY
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---
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@ -19,7 +19,7 @@ question:
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answers:
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- It uses probability distributions to predict future events or states.
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- It analyzes the relationship between independent and dependent variables to make predictions.
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- It separates data points into separate categories.
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- It separates data points into separate categories.
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solution: 1
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```
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id: 5e8f2f13c4cdbe86b5c72d8c
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title: 'Core Learning Algorithms: The Training Process'
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challengeType: 11
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isHidden: true
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isHidden: false
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videoId: _cEwvqVoBhI
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---
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id: 5e8f2f13c4cdbe86b5c72d8b
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title: 'Core Learning Algorithms: Training and Testing Data'
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challengeType: 11
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isHidden: true
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isHidden: false
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videoId: wz9J1slsi7I
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---
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id: 5e8f2f13c4cdbe86b5c72d91
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title: 'Core Learning Algorithms: Using Probabilities to make Predictions'
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challengeType: 11
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isHidden: true
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isHidden: false
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videoId: fYAYvLUawnc
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---
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id: 5e8f2f13c4cdbe86b5c72d8a
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title: 'Core Learning Algorithms: Working with Data'
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challengeType: 11
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isHidden: true
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isHidden: false
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videoId: u85IOSsJsPI
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---
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id: 5e8f2f13c4cdbe86b5c72d89
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title: Core Learning Algorithms
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challengeType: 11
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isHidden: true
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isHidden: false
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videoId: u5lZURgcWnU
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---
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@ -16,8 +16,8 @@ videoId: u5lZURgcWnU
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```yml
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question:
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text: |
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Which type of analysis would be best suited for the following problem?:
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Which type of analysis would be best suited for the following problem?:
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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.
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answers:
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- Multiple regression
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id: 5e8f2f13c4cdbe86b5c72d98
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title: Creating a Convolutional Neural Network
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challengeType: 11
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isHidden: true
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isHidden: false
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videoId: kfv0K8MtkIc
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---
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id: 5e8f2f13c4cdbe86b5c72d87
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title: "Introduction: Machine Learning Fundamentals"
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challengeType: 11
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isHidden: true
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isHidden: false
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videoId: KwL1qTR5MT8
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---
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id: 5e8f2f13c4cdbe86b5c72d88
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title: Introduction to TensorFlow
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challengeType: 11
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isHidden: true
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isHidden: false
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videoId: r9hRyGGjOgQ
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---
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id: 5e8f2f13c4cdbe86b5c72da1
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title: 'Natural Language Processing With RNNs: Building the Model'
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challengeType: 11
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isHidden: true
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isHidden: false
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videoId: 32WBFS7lfsw
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---
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def build_mode(vocab_size, embedding_dim, rnn_units, batch_size):
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model = tf.keras.Sequential([
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tf.keras.layers.Embedding(vocab_size,
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embedding_dim,
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embedding_dim,
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batch_input_shape=[batch_size, None]),
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tf.keras.layers.__A__(rnn_units,
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return_sequences=__B__,
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id: 5e8f2f13c4cdbe86b5c72da0
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title: 'Natural Language Processing With RNNs: Create a Play Generator'
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challengeType: 11
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isHidden: true
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isHidden: false
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videoId: j5xsxjq_Xk8
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---
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id: 5e8f2f13c4cdbe86b5c72d9f
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title: 'Natural Language Processing With RNNs: Making Predictions'
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challengeType: 11
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isHidden: true
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isHidden: false
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videoId: WO1hINnBj20
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---
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id: 5e8f2f13c4cdbe86b5c72d9c
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title: 'Natural Language Processing With RNNs: Part 2'
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challengeType: 11
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isHidden: true
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isHidden: false
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videoId: mUU9YXOFbZg
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---
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id: 5e8f2f13c4cdbe86b5c72d9d
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title: 'Natural Language Processing With RNNs: Recurring Neural Networks'
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challengeType: 11
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isHidden: true
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isHidden: false
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videoId: bX5681NPOcA
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---
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id: 5e8f2f13c4cdbe86b5c72d9e
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title: 'Natural Language Processing With RNNs: Sentiment Analysis'
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challengeType: 11
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isHidden: true
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isHidden: false
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videoId: lYeLtu8Nq7c
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---
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id: 5e8f2f13c4cdbe86b5c72da2
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title: 'Natural Language Processing With RNNs: Training the Model'
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challengeType: 11
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isHidden: true
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isHidden: false
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videoId: hEUiK7j9UI8
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---
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id: 5e8f2f13c4cdbe86b5c72d9b
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title: Natural Language Processing With RNNs
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challengeType: 11
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isHidden: true
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isHidden: false
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videoId: ZyCaF5S-lKg
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---
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id: 5e8f2f13c4cdbe86b5c72d93
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title: 'Neural Networks: Activation Functions'
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challengeType: 11
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isHidden: true
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isHidden: false
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videoId: S45tqW6BqRs
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---
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id: 5e8f2f13c4cdbe86b5c72d95
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title: 'Neural Networks: Creating a Model'
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challengeType: 11
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isHidden: true
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isHidden: false
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videoId: K8bz1bmOCTw
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---
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answers:
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- |
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A: `keras`
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B: `Sequential`
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C: `Dense`
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A: `tf`
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B: `Sequential`
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C: `Categorical`
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- |
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A: `keras`
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B: `sequential`
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C: `dense`
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solution: 1
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```
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id: 5e8f2f13c4cdbe86b5c72d94
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title: 'Neural Networks: Optimizers'
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challengeType: 11
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isHidden: true
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isHidden: false
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videoId: hdOtRPQe1o4
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---
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id: 5e8f2f13c4cdbe86b5c72d92
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title: Neural Networks with TensorFlow
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challengeType: 11
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isHidden: true
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isHidden: false
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videoId: uisdfrNrZW4
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---
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id: 5e8f2f13c4cdbe86b5c72da5
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title: 'Reinforcement Learning With Q-Learning: Example'
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challengeType: 11
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isHidden: true
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isHidden: false
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videoId: RBBSNta234s
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---
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id: 5e8f2f13c4cdbe86b5c72da4
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title: 'Reinforcement Learning With Q-Learning: Part 2'
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challengeType: 11
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isHidden: true
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isHidden: false
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videoId: DX7hJuaUZ7o
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---
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id: 5e8f2f13c4cdbe86b5c72da3
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title: Reinforcement Learning With Q-Learning
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challengeType: 11
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isHidden: true
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isHidden: false
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videoId: Cf7DSU0gVb4
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---
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