Complete Guide to TensorFlow for Deep Learning with Python 

Introduction

Course Overview -- PLEASE DON'T SKIP THIS LECTURE! Thanks :)

FAQ - Frequently Asked Questions

Quick Note for MacOS and Linux Users

Installing TensorFlow and Environment Setup

Machine Learning Overview

Crash Course Section Introduction

NumPy Crash Course

Pandas Crash Course

Data Visualization Crash Course

SciKit Learn Preprocessing Overview

Crash Course Review Exercise

Crash Course Review Exercise - Solutions

Neural Network Basics - Helpful Resources

Introduction to Neural Networks

Introduction to Perceptron

Neural Network Activation Functions

Cost Functions

Gradient Descent Backpropagation

TensorFlow Playground

Manual Creation of Neural Network - Part One

Manual Creation of Neural Network - Part Two - Operations

Manual Creation of Neural Network - Part Three - Placeholders and Variables

Manual Creation of Neural Network - Part Four - Session

Manual Neural Network Classification Task

Neural Networks - FAQ and Closing Thoughts

TensorFlow Basics - Helpful Resources

Introduction to TensorFlow

TensorFlow Basic Syntax

TensorFlow Graphs

Variables and Placeholders

TensorFlow - A Neural Network - Part One

TensorFlow - A Neural Network - Part Two

TensorFlow Regression Example - Part One

TensorFlow Regression Example _ Part Two

TensorFlow Regression Example - Part Two

TensorFlow Classification Example - Part One

TensorFlow Classification Example - Part Two

TF Regression Exercise

TF Regression Exercise Solution Walkthrough

TF Classification Exercise

TF Classification Exercise Solution Walkthrough

Saving and Restoring Models

TensorFlow Basics - FAQ and Closing Thoughts

Convolutional Neural Networks - Helpful Resources

Introduction to Convolutional Neural Network Section

Review of Neural Networks

New Theory Topics

Quick note on MNIST lecture

MNIST Data Overview

MNIST Basic Approach Part One

MNIST Basic Approach Part Two

CNN Theory Part One

CNN Theory Part Two

CNN MNIST Code Along - Part One

CNN MNIST Code Along - Part Two

Introduction to CNN Project

CNN Project Exercise Solution - Part One

CNN Project Exercise Solution - Part Two

CNN - FAQ and Closing Thoughts

Recurrent Neural Networks - Helpful Resources

Introduction to RNN Section

RNN Theory

Manual Creation of RNN

Vanishing Gradients

LSTM and GRU Theory

Introduction to RNN with TensorFlow API

RNN with TensorFlow - Part One

RNN with TensorFlow - Part Two

Quick Note on RNN Plotting Part 3

RNN with TensorFlow - Part Three

Time Series Exercise Overview

Time Series Exercise Solution

Quick Note on Word2Vec

Word2Vec Theory

Word2Vec Code Along - Part One

Word2Vec Part Two

RNN- FAQ and Closing Thoughts

Intro to Miscellaneous Topics

Deep Nets with Tensorflow Abstractions API - Part One

Deep Nets with Tensorflow Abstractions API - Estimator API

Deep Nets with Tensorflow Abstractions API - Keras

Deep Nets with Tensorflow Abstractions API - Layers

Tensorboard

Autoencoders - Helpful Resources

Introduction to Autoencoders

Autoencoder Basics

Dimensionality Reduction with Linear Autoencoder

Linear Autoencoder PCA Exercise Overview

Linear Autoencoder PCA Exercise Solutions

Stacked Autoencoder

Introduction to GAN

Introduction to Reinforcement Learning with OpenAI Gym

Extra Resources for Reinforcement Learning

Introduction to OpenAI Gym

OpenAI Gym Steup

Open AI Gym Env Basics

Open AI Gym Observations

OpenAI Gym Actions

Simple Neural Network Game

Policy Gradient Theory

Policy Gradient Code Along Part One

Policy Gradient Code Along Part Two

Introduction to GANs

GAN Code Along - Part One

GAN Code Along - Part Two

GAN Code Along - Part Three

Bonus Lecture