HRDF Course- Deep Learning and Machine Learning with TensorFlow

Tensorflow is the most popular and powerful open source machine learning/deep learning framework developed by Google for everyone. Tensorflow has many powerful Machine Learning API such as Neural Network, Convolutional Neural Network (CNN), Recurrent Neural Network (RNN),  Word Embedding, Seq2Seq, Generative Adversarial Networks (GAN), Reinforcement Learning, and Meta Learning. This course will show you how to build deep learning applications using Tensorflow.

The topics include

• Installing TensorFlow
• Math Operations with TensorFlow
• Neural Networks with TensorFlow
• Deep Learning with Tensorflow
• Image Recognition with Convolutional Neural Network (CNN)
• Text Analysis with Recurrent Neural Network (RNN)
• Keras
• Eager Mode

Day 1

Module 1 Getting Started

• Overview of AI and Machine Learing 
• What is TensorFlow?
• Tensor and Data Types
• Install and Run TensorFlow

Module 2 Basic Tensorflow Operations

• Graph and Session
• Math Operations
• Matrix
• Graph Operations
• Placeholder
• Variable

Module 3 Datasets

• MNIST Handwritten Digits Dataset
• CIFAR Image Dataset
• One Hot Encoding/Decoding

Module 4 Machine Learning

• Machine Learning Approach - Loss, Optimizer, Train
• ML on Linear Regression
• ML on Classification
• Softmax and Cross Entropy
• Save and Load Model

Module 5 Neural Network (NN)

• What is Neural Network 
• Activation Functions
• Why Deep Learning?
• Neural Network for Handwritten Digit MNIST Dataset

Day 2

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 Basic Keras

• What is Keras?
• NN with Keras
• Tensorboard Callback 
• CNN with Keras
• Transfer Learning 
• RNN with Keras

Module 10 TF.Data and Estimators (Optional)

• What is TF.Data?
• ETL Pipeline
• TFRecords
• What is Estimator?
• Feature Columns and Input Function
• Regression Estimator
• Classification Estimator