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AI: Deep Learning with TensorFlow
Section 1 Welcome
Lecture 1 Welcome (2:14)
Lecture 2 Installing TensorFlow (5:30)
Lecture 3 Simple Computations (5:31)
Lecture 4 Logistic Regression Model Building (6:58)
Lecture 5 Logistic Regression Training (4:53)
Section 2 Deep Neural Networks
Lecture 6 Basic Neural Nets (5:01)
Lecture 7 Single Hidden Layer Model (5:05)
Lecture 8 Single Hidden Layer Explained (4:32)
Lecture 9 Multiple Hidden Layer Model (5:20)
Lecture 10 Multiple Hidden Layer Results (4:42)
Section 3 Convolutional Neural Networks
Lecture 11 Convolutional Layer Motivation (5:04)
Lecture 12 Convolutional Layer Application (6:55)
Lecture 13 Pooling Layer Motivation (3:49)
Lecture 14 Pooling Layer Application (4:07)
Lecture 15 Deep CNN (6:19)
Lecture 16 Deeper CNN (3:56)
Lecture 17 Wrapping Up Deep CNN (4:40)
Section 4 Recurrent Neural Networks
Lecture 18 Recurrent Neural Networks (8:49)
Lecture 19 skflow (9:18)
Lecture 20 RNNs in skflow (4:04)
Section 5 Outro
Lecture 21 Research Evaluation (6:55)
Lecture 22 The Future of TensorFlow (4:15)
Working Files
Working Files
Lecture 22 The Future of TensorFlow
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