These are the exercise files used for Deep Learning and Machine Learning with TensorFlow course.
The course outline can be found in
https://www.tertiarycourses.com.sg/deep-learning-neural-network-tensorflow.html
https://www.tertiarycourses.com.my/deep-learning-neural-network-tensorflow-malaysia.html
Module 1 Getting Started
- What is TensorFlow
- Install and Run TensorFlow
Module 2 Basic Tensorflow Operations
- Constant
- Graph Operation
- Math
- Matrix
- Placeholder
- Variable
Module 3 Datasets
- MNIST Handwritten Digits Dataset
- CIFAR Image Dataset
- One Hot Encoding/Decoding
- Split Dataset to Training/Testing
Module 4 Machine Learning on TF
- Regression ML Model
- Loss Function
- Optimizer
- Training
- Save and Load Model
Module 5 Neural Network (NN)
- What is Neural Network
- Activation Functions
- Deep Neural Network on MNIST
Module 6 Tensorboard
- What is Tensorboard?
- Visualize a Tensorboard Graph
- Output Data to Tensorboard
Module 7 Convolutional Neural Network (CNN)
- What is CNN?
- CNN Architecture
- Convolution Layers
- Pooling and Dropout Layers
- CNN on MNIST dataset
Module 8 Recurrent Neural Network (RNN)
- Sequential Data
- What is RNN?
- Types of RNN
- How to train a RNN
- Long Term Dependencies
- LSTM and GRU Cells
- RNN on IMDB dataset
Module 9 Keras
- What is Keras?
- NN with Keras
- CNN with Keras
- Transfer Learning with Keras
- RNN with Keras
Module 10 Appendix (Optional)
- TF Estimators
- Eager Mode