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[Python] Deep Learning
Introduction
1.1.2. AI, ML and DL Introduction (12:00)
1.1.1. AI, ML and DL Introduction (8:36)
1.1.3. AI, ML and DL introduction (14:16)
1.2.1. Practise 1 - TensorFlow Fundamental (16:15)
1.2.2. Practise 2 - TensorFlow Fundamental (24:41)
1.2.3. Practise 3 - TensorFlow Fundamental (24:24)
Perceptron
2.1.1. Perceptron 1 (18:50)
2.1.2. Perceptron 2 (20:55)
2.2. Training Neural Network Model (25:59)
2.3. Neural Network Playground (5:58)
2.4.1. Practise 1 - Simple Example with TensorFlow (19:58)
2.4.2. Practise 2 - Simple Example with TensorFlow (7:48)
2.4.3. Practise 3 - Simple Example with TensorFlow (8:39)
2.5.1. Practise 1 - Beginning with Digit Recognizer (13:25)
2.5.2. Practise 2 - Beginning with Digit Recognizer (19:52)
2.5.3. Practise 3 - Beginning with Digit Recognizer (10:11)
2.5.4. Practise 4 - Beginning with Digit Recognizer (14:21)
2.6. Practise - Digit Recognizer with Keras (17:17)
Convolutional Neural Network
3.1. Introduction (1:49)
3.2.1. Layers in CNN (12:22)
3.2.2. Transfer Learning (4:38)
3.3. Application of CNN (5:42)
3.4.1. Practise 1 - How to implement CNN with TensorFlow (19:18)
3.4.2. Practise 2 - How to implement CNN with TensorFLow (19:49)
3.4.3. Practise 3 - How to implement CNN with TensorFlow (19:26)
3.5. Practise - Classify Images of Clothing with CNN and Keras (16:13)
3.6.1. Practise 1 - Transfer Learning with Keras (7:55)
3.6.2. Practise 2 - Transfer Learning with Keras (16:07)
Recurrent Neural Network
4.1. Introduction to Recurrent Neural Network (5:02)
4.2. Traditional RNN Structure (8:00)
4.3. Practise - Understanding traditional RNN Structure (16:08)
4.4.1. LTSM 1 (9:08)
4.4.2. LSTM 2 (8:25)
4.5. Application of RNN (11:48)
4.6.1. Practise 1 - Classify text comment with RNN (20:04)
4.6.2. Practise 2 - Classify text comment with RNN (10:56)
Summary
5.1. Review Cerificate Exam (9:19)
3.4.1. Practise 1 - How to implement CNN with TensorFlow
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