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Complete Guide to TensorFlow for Deep Learning with Python

Video Introducing this tutorial


Introduction :
Introduction
Course Overview -- PLEASE DON'T SKIP THIS LECTURE! Thanks :)
FAQ - Frequently Asked Questions

Installation and Setup :
Quick Note for MacOS and Linux Users
Installing TensorFlow Environment

What is Machine Learning? :
Machine Learning Overview

Crash Course 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

Introduction to Neural Networks :
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

TensorFlow Basics :
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 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

Convolutional Neural Networks :
Introduction to Convolutional Neural Network Section
Review of Neural Networks
New Theory Topics
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

Recurrent Neural Networks :
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

Miscellaneous Topics :
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 :
Autoencoder Basics
Dimensionality Reduction with Linear Autoencoder
Linear Autoencoder PCA Exercise Overview
Linear Autoencoder PCA Exercise Solutions
Stacked Autoencoder

Reinforcement Learning with OpenAI Gym :
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

GAN - Generative Adversarial Networks :
Introduction to GANs
GAN Code Along - Part One
GAN Code Along - Part Two
GAN Code Along - Part Three

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