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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 .