Tensorflow getting started book

Tensorflow Quick Introduction

• Every chapter consist in directory with it's name

• Book chapters

1- Tensorflow basic concept

• Install
• What is shape ?
• What is tensor
• Getting started with basic tensors
• Tensorboard
• Lazy computing idea behind sessions

2- Doing math with tensorflow

• Juila set
• Monte carlo algorithm
• Normal Distribution
• Uniform Distribution

3- Starting with machine learning

• linear regression algorithm with cost function Gradient decent
• Mnist data set
• Classification using K-nearest neighbour KNN algorithm for
• Cluster using K-means algorithm .

4- Introduction to Neural network

• Image classification for mnist dataset using linear regression and neural network using single layer perception.
• Multi Layer Perception neural network with Adam algorithm
• Multi layer approximation function

5- Deep learning

• Image classification problem using Convolution neural network .
• NLP problem using recurrent neural network .