/deeplearning-tf

Courses, tutorials and examples of Deep Learning with TensorFlow

Primary LanguageJupyter NotebookMIT LicenseMIT

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
  1. Install the dependencies (conda environments are recommended):
$ cd deeplearning-tf
$ pip install -r requirements.txt
  1. Run a Jupyter Notebook to navigate and execute the code:
$ jupyter notebook