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deeplearning-tf's Introduction

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 โ€“ Convolutional Neural Networks (CNN)

    • Understanding CNNs
    • CNN Application
  • Module 3 โ€“ 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

deeplearning-tf's People

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