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Sl.No Chapter Name MP4 Download Transcript Download
1Overview of TensorflowDownloadDownload
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2Machine Learning RefresherDownloadDownload
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3Steps in Machine Learning ProcessDownloadDownload
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4Loss Functions in Machine LearningDownloadDownload
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5Gradient DescentDownloadDownload
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6Gradient Descent VariationsDownloadDownload
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7Model Selection and EvaluationDownloadDownload
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8Machine Learning VisualizationDownloadDownload
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9Deep Learning RefresherDownloadDownload
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10Introduction to TensorsDownloadDownload
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11Mathematical Foundations of Deep Learning - Contd.DownloadDownload
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12Building Data Pipelines for Tensorflow-Part 1DownloadDownload
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13Building Data Pipelines for Tensorflow-Part 2DownloadDownload
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14Building Data Pipelines for Tensorflow-Part 3DownloadDownload
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15Text Processing with TensorflowDownloadDownload
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16Classify ImagesDownloadDownload
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17RegressionDownloadDownload
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18Classify Structured DataDownloadDownload
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19Text ClassificationDownloadDownload
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20Underfitting and OverfittingDownloadDownload
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21Save and Restore ModelsDownloadDownload
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22CNNs-Part 1DownloadDownload
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23CNNs-Part 2DownloadDownload
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24Transfer learning with pretrained CNNsDownloadDownload
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25Transfer learning with TF hubDownloadDownload
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26Image classification and visualizationDownloadDownload
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27Estimator APIDownloadDownload
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28Logistic RegressionDownloadDownload
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29Boosted TreesDownloadDownload
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30Introduction to word embeddingsDownloadDownload
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31Recurrent Neural Networks (Part 1)DownloadDownload
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32Recurrent Neural Networks (Part 2)DownloadDownload
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33Time Series Forecasting with RNNsDownloadDownload
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34Text Generation with RNNs.DownloadDownload
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35TensorFlow CustomizationDownloadDownload
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36Customizing tf.keras - Part 1DownloadDownload
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37Customizing tf.keras - Part 2DownloadDownload
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38TensorFlow Distributed TrainingDownloadDownload
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