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What you’ll learn
- Understand how Neural Networks Work
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Build your own Neural Network from Scratch with Python
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Use TensorFlow for Classification and Regression Tasks
- Use TensorFlow for Image Classification with Convolutional Neural Networks
- Use TensorFlow for Time Series Analysis with Recurrent Neural Networks
- Use TensorFlow for solving Unsupervised Learning Problems with AutoEncoders
- Learn how to conduct Reinforcement Learning with OpenAI Gym
- Create Generative Adversarial Networks with TensorFlow
- Become a Deep Learning Guru!
Course Curriculum
01 Introduction | |||
001 Introduction | 00:00:00 | ||
002 Course Overview — PLEASE DON’T SKIP THIS LECTURE! Thanks _) | 00:00:00 | ||
003 FAQ – Frequently Asked Questions | 00:00:00 | ||
Downloads | 00:00:00 | ||
02 Installation and Setup | |||
004 Quick Note for MacOS and Linux Users | 00:00:00 | ||
005 Installing TensorFlow Environment | 00:00:00 | ||
03 What is Machine Learning_ | |||
006 Machine Learning Overview | 00:00:00 | ||
04 Crash Course Overview | |||
007 Crash Course Section Introduction | 00:00:00 | ||
008 NumPy Crash Course | 00:00:00 | ||
009 Pandas Crash Course | 00:00:00 | ||
010 Data Visualization Crash Course | 00:00:00 | ||
011 SciKit Learn Preprocessing Overview | 00:00:00 | ||
012 Crash Course Review Exercise | 00:00:00 | ||
013 Crash Course Review Exercise – Solutions | 00:00:00 | ||
05 Introduction to Neural Networks | |||
014 Introduction to Neural Networks | 00:00:00 | ||
015 Introduction to Perceptron | 00:00:00 | ||
016 Neural Network Activation Functions | 00:00:00 | ||
017 Cost Functions | 00:00:00 | ||
018 Gradient Descent Backpropagation | 00:00:00 | ||
019 TensorFlow Playground | 00:00:00 | ||
020 Manual Creation of Neural Network – Part One | 00:00:00 | ||
021 Manual Creation of Neural Network – Part Two – Operations | 00:00:00 | ||
022 Manual Creation of Neural Network – Part Three – Placeholders and Variables | 00:00:00 | ||
023 Manual Creation of Neural Network – Part Four – Session | 00:00:00 | ||
024 Manual Neural Network Classification Task | 00:00:00 | ||
06 TensorFlow Basics | |||
025 Introduction to TensorFlow | 00:00:00 | ||
026 TensorFlow Basic Syntax | 00:00:00 | ||
027 TensorFlow Graphs | 00:00:00 | ||
028 Variables and Placeholders | 00:00:00 | ||
029 TensorFlow – A Neural Network – Part One | 00:00:00 | ||
030 TensorFlow – A Neural Network – Part Two | 00:00:00 | ||
031 TensorFlow Regression Example – Part One | 00:00:00 | ||
032 TensorFlow Regression Example _ Part Two | 00:00:00 | ||
033 TensorFlow Classification Example – Part One | 00:00:00 | ||
034 TensorFlow Classification Example – Part Two | 00:00:00 | ||
035 TF Regression Exercise | 00:00:00 | ||
036 TF Regression Exercise Solution Walkthrough | 00:00:00 | ||
037 TF Classification Exercise | 00:00:00 | ||
038 TF Classification Exercise Solution Walkthrough | 00:00:00 | ||
039 Saving and Restoring Models | 00:00:00 | ||
07 Convolutional Neural Networks | |||
040 Introduction to Convolutional Neural Network Section | 00:00:00 | ||
041 Review of Neural Networks | 00:00:00 | ||
042 New Theory Topics | 00:00:00 | ||
044 MNIST Data Overview | 00:00:00 | ||
045 MNIST Basic Approach Part One | 00:00:00 | ||
046 MNIST Basic Approach Part Two | 00:00:00 | ||
047 CNN Theory Part One | 00:00:00 | ||
048 CNN Theory Part Two | 00:00:00 | ||
049 CNN MNIST Code Along – Part One | 00:00:00 | ||
050 CNN MNIST Code Along – Part Two | 00:00:00 | ||
051 Introduction to CNN Project | 00:00:00 | ||
052 CNN Project Exercise Solution – Part One | 00:00:00 | ||
053 CNN Project Exercise Solution – Part Two | 00:00:00 | ||
08 Recurrent Neural Networks | |||
054 Introduction to RNN Section | 00:00:00 | ||
055 RNN Theory | 00:00:00 | ||
056 Manual Creation of RNN | 00:00:00 | ||
057 Vanishing Gradients | 00:00:00 | ||
058 LSTM and GRU Theory | 00:00:00 | ||
059 Introduction to RNN with TensorFlow API | 00:00:00 | ||
060 RNN with TensorFlow – Part One | 00:00:00 | ||
061 RNN with TensorFlow – Part Two | 00:00:00 | ||
062 Quick Note on RNN Plotting Part 3 | 00:00:00 | ||
063 RNN with TensorFlow – Part Three | 00:00:00 | ||
064 Time Series Exercise Overview | 00:00:00 | ||
065 Time Series Exercise Solution | 00:00:00 | ||
066 Quick Note on Word2Vec | 00:00:00 | ||
067 Word2Vec Theory | 00:00:00 | ||
068 Word2Vec Code Along – Part One | 00:00:00 | ||
069 Word2Vec Part Two | 00:00:00 | ||
09 Miscellaneous Topics | |||
070 Intro to Miscellaneous Topics | 00:00:00 | ||
071 Deep Nets with Tensorflow Abstractions API – Part One | 00:00:00 | ||
072 Deep Nets with Tensorflow Abstractions API – Estimator API | 00:00:00 | ||
073 Deep Nets with Tensorflow Abstractions API – Keras | 00:00:00 | ||
074 Deep Nets with Tensorflow Abstractions API – Layers | 00:00:00 | ||
10 AutoEncoders | |||
076 Autoencoder Basics | 00:00:00 | ||
077 Dimensionality Reduction with Linear Autoencoder | 00:00:00 | ||
078 Linear Autoencoder PCA Exercise Overview | 00:00:00 | ||
079 Linear Autoencoder PCA Exercise Solutions | 00:00:00 | ||
080 Stacked Autoencoder | 00:00:00 | ||
11 Reinforcement Learning with OpenAI Gym | |||
081 Introduction to Reinforcement Learning with OpenAI Gym | 00:00:00 | ||
082 Extra Resources for Reinforcement Learning | 00:00:00 | ||
083 Introduction to OpenAI Gym | 00:00:00 | ||
084 OpenAI Gym Steup | 00:00:00 | ||
085 Open AI Gym Env Basics | 00:00:00 | ||
086 Open AI Gym Observations | 00:00:00 | ||
087 OpenAI Gym Actions | 00:00:00 | ||
088 Simple Neural Network Game | 00:00:00 | ||
089 Policy Gradient Theory | 00:00:00 | ||
090 Policy Gradient Code Along Part One | 00:00:00 | ||
091 Policy Gradient Code Along Part Two | 00:00:00 | ||
12 GAN - Generative Adversarial Networks | |||
092 Introduction to GANs | 00:00:00 | ||
093 GAN Code Along – Part One | 00:00:00 | ||
094 GAN Code Along – Part Two | 00:00:00 | ||
095 GAN Code Along – Part Three | 00:00:00 | ||
13 BONUS | |||
096 Bonus Lecture_ Discounts for for My Other Courses | 00:00:00 |
7 STUDENTS ENROLLED