Deep Learning with TensorFlow

This repository contains course materials, tutorials and examples about Deep Learning with TensorFlow.

Contents of the repository

Deep Learning with TensorFlow - Big Data University

Folder

dl_tf_BDU

Syllabus

• Module 1 - Introduction to TensorFlow

  • HelloWorld with TensorFlow
  • Linear Regression
  • Nonlinear Regression
  • Logistic Regression
  • Activation Functions

• Module 2 – Convolutional Neural Networks (CNN)

  • Understanding CNNs
  • CNN Application

• Module 3 – Recurrent Neural Networks (RNN)

  • Intro to RNN Model
  • Long Short-Term memory (LSTM)
  • Recursive Neural Tensor Network Theory
  • Recurrent Neural Network Model

• Module 4 - Unsupervised Learning

  • Applications of Unsupervised Learning
  • Restricted Boltzmann Machine
  • Collaborative Filtering with RBM

• Module 5 - Autoencoders

  • Introduction to Autoencoders and Applications
  • Autoencoders
  • Deep Belief Network

How to run the code

The code was tested in Python 3.5, but it should probably work in Python 2.7 too.

1. Clone the repository:

$ git clone https://github.com/santipuch590/deeplearning-tf.git

2. Install the dependencies (conda environments are recommended):

$ cd deeplearning-tf
$ pip install -r requirements.txt

3. Run a Jupyter Notebook to navigate and execute the code:

$ jupyter notebook