142 lines
3.4 KiB
JSON
142 lines
3.4 KiB
JSON
{
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"name": "TensorFlow",
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"isUpcomingChange": false,
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"dashedName": "tensorflow",
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"order": 1,
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"time": "15 hours",
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"superBlock": "machine-learning-with-python",
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"superOrder": 10,
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"challengeOrder": [
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[
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"5e8f2f13c4cdbe86b5c72d87",
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"Introduction: Machine Learning Fundamentals"
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],
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[
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"5e8f2f13c4cdbe86b5c72d88",
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"Introduction to TensorFlow"
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],
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[
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"5e8f2f13c4cdbe86b5c72d89",
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"Core Learning Algorithms"
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],
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[
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"5e8f2f13c4cdbe86b5c72d8a",
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"Core Learning Algorithms: Working with Data"
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],
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[
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"5e8f2f13c4cdbe86b5c72d8b",
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"Core Learning Algorithms: Training and Testing Data"
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],
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[
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"5e8f2f13c4cdbe86b5c72d8c",
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"Core Learning Algorithms: The Training Process"
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],
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[
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"5e8f2f13c4cdbe86b5c72d8d",
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"Core Learning Algorithms: Classification"
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],
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[
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"5e8f2f13c4cdbe86b5c72d8e",
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"Core Learning Algorithms: Building the Model"
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],
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[
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"5e8f2f13c4cdbe86b5c72d8f",
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"Core Learning Algorithms: Clustering"
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],
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[
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"5e8f2f13c4cdbe86b5c72d90",
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"Core Learning Algorithms: Hidden Markov Models"
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],
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[
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"5e8f2f13c4cdbe86b5c72d91",
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"Core Learning Algorithms: Using Probabilities to make Predictions"
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],
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[
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"5e8f2f13c4cdbe86b5c72d92",
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"Neural Networks with TensorFlow"
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],
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[
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"5e8f2f13c4cdbe86b5c72d93",
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"Neural Networks: Activation Functions"
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],
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[
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"5e8f2f13c4cdbe86b5c72d94",
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"Neural Networks: Optimizers"
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],
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[
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"5e8f2f13c4cdbe86b5c72d95",
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"Neural Networks: Creating a Model"
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],
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[
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"5e8f2f13c4cdbe86b5c72d96",
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"Convolutional Neural Networks"
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],
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[
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"5e8f2f13c4cdbe86b5c72d97",
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"Convolutional Neural Networks: The Convolutional Layer"
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],
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[
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"5e8f2f13c4cdbe86b5c72d98",
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"Creating a Convolutional Neural Network"
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],
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[
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"5e8f2f13c4cdbe86b5c72d99",
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"Convolutional Neural Networks: Evaluating the Model"
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],
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[
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"5e8f2f13c4cdbe86b5c72d9a",
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"Convolutional Neural Networks: Picking a Pretrained Model"
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],
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[
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"5e8f2f13c4cdbe86b5c72d9b",
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"Natural Language Processing With RNNs"
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],
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[
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"5e8f2f13c4cdbe86b5c72d9c",
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"Natural Language Processing With RNNs: Part 2"
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],
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[
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"5e8f2f13c4cdbe86b5c72d9d",
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"Natural Language Processing With RNNs: Recurring Neural Networks"
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],
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[
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"5e8f2f13c4cdbe86b5c72d9e",
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"Natural Language Processing With RNNs: Sentiment Analysis"
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],
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[
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"5e8f2f13c4cdbe86b5c72d9f",
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"Natural Language Processing With RNNs: Making Predictions"
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],
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[
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"5e8f2f13c4cdbe86b5c72da0",
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"Natural Language Processing With RNNs: Create a Play Generator"
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],
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[
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"5e8f2f13c4cdbe86b5c72da1",
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"Natural Language Processing With RNNs: Building the Model"
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],
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[
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"5e8f2f13c4cdbe86b5c72da2",
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"Natural Language Processing With RNNs: Training the Model"
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],
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[
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"5e8f2f13c4cdbe86b5c72da3",
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"Reinforcement Learning With Q-Learning"
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],
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[
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"5e8f2f13c4cdbe86b5c72da4",
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"Reinforcement Learning With Q-Learning: Part 2"
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],
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[
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"5e8f2f13c4cdbe86b5c72da5",
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"Reinforcement Learning With Q-Learning: Example"
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],
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[
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"5e8f2f13c4cdbe86b5c72da6",
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"Conclusion"
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]
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],
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"helpRoom": "Help",
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"fileName": "11-machine-learning-with-python/lectures-tensorflow.json"
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}
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