IIRF Online > Development > Data Science > Deep Learning > Tensorflow 2.0: Deep Learning and Artificial Intelligence
Tensorflow 2.0: Deep Learning and Artificial Intelligence by Udemy
Machine Learning & Neural Networks for Computer Vision, Time Series Analysis, NLP, GANs, Reinforcement Learning, +More!
Course Highlights
- Artificial Neural Networks (ANNs) / Deep Neural Networks (DNNs)
- Predict Stock Returns
- Time Series Forecasting
- Computer Vision
- How to build a Deep Reinforcement Learning Stock Trading Bot
- GANs (Generative Adversarial Networks)
- Recommender Systems
- Image Recognition
- Convolutional Neural Networks (CNNs)
- Recurrent Neural Networks (RNNs)
- Use Tensorflow Serving to serve your model using a RESTful API
- Use Tensorflow Lite to export your model for mobile (Android, iOS) and embedded devices
- Use Tensorflow's Distribution Strategies to parallelize learning
- Low-level Tensorflow, gradient tape, and how to build your own custom models
- Natural Language Processing (NLP) with Deep Learning
- Demonstrate Moore's Law using Code
- Transfer Learning to create state-of-the-art image classifiers
Skills you will learn!
Curriculum
4 Topics
Introduction
Outline
Get Your Hands Dirty Practical Coding Experience Data Links
Where to get the code notebooks and data
6 Topics
Intro to Google Colab how to use a GPU or TPU for free
Tensorflow 2.0 in Google Colab
Uploading your own data to Google Colab
Where can I learn about Numpy Scipy Matplotlib Pandas and Scikit-Learn?
How to Succeed in This Course
Temporary 403 Errors
11 Topics
What is Machine Learning?
Code Preparation (Classification Theory)
Classification Notebook
Code Preparation (Regression Theory)
Regression Notebook
The Neuron
How does a model "learn"?
Making Predictions
Saving and Loading a Model
Why Keras?
Suggestion Box
11 Topics
Artificial Neural Networks Section Introduction
Beginners Rejoice: The Math in This Course is Optional
Forward Propagation
The Geometrical Picture
Activation Functions
Multiclass Classification
How to Represent Images
Color Mixing Clarification
Code Preparation (ANN)
ANN for Image Classification
ANN for Regression
11 Topics
What is Convolution? (part 1)
What is Convolution? (part 2)
What is Convolution? (part 3)
Convolution on Color Images
CNN Architecture
CNN Code Preparation
CNN for Fashion MNIST
CNN for CIFAR-10
Data Augmentation
Batch Normalization
Improving CIFAR-10 Results
18 Topics
Sequence Data
Forecasting
Autoregressive Linear Model for Time Series Prediction
Proof that the Linear Model Works
Recurrent Neural Networks
RNN Code Preparation
RNN for Time Series Prediction
Paying Attention to Shapes
GRU and LSTM (pt 1)
GRU and LSTM (pt 2)
A More Challenging Sequence
Demo of the Long Distance Problem
RNN for Image Classification (Theory)
RNN for Image Classification (Code)
Stock Return Predictions using LSTMs (pt 1)
Stock Return Predictions using LSTMs (pt 2)
Stock Return Predictions using LSTMs (pt 3)
Other Ways to Forecast
6 Topics
Embeddings
Code Preparation (NLP)
Text Preprocessing
Text Classification with LSTMs
CNNs for Text
Text Classification with CNNs
2 Topics
Recommender Systems with Deep Learning Theory
Recommender Systems with Deep Learning Code
6 Topics
Transfer Learning Theory
Some Pre-trained Models (VGG ResNet Inception MobileNet)
Large Datasets and Data Generators
2 Approaches to Transfer Learning
Transfer Learning Code (pt 1)
Transfer Learning Code (pt 2)
2 Topics
GAN Theory
GAN Code
14 Topics
Deep Reinforcement Learning Section Introduction
Elements of a Reinforcement Learning Problem
States Actions Rewards Policies
Markov Decision Processes (MDPs)
The Return
Value Functions and the Bellman Equation
What does it mean to “learn”?
Solving the Bellman Equation with Reinforcement Learning (pt 1)
Solving the Bellman Equation with Reinforcement Learning (pt 2)
Epsilon-Greedy
Q-Learning
Deep Q-Learning / DQN (pt 1)
Deep Q-Learning / DQN (pt 2)
How to Learn Reinforcement Learning
10 Topics
Reinforcement Learning Stock Trader Introduction
Data and Environment
Replay Buffer
Program Design and Layout
Code pt 1
Code pt 2
Code pt 3
Code pt 4
Reinforcement Learning Stock Trader Discussion
Help! Why is the code slower on my machine?
6 Topics
What is a Web Service? (Tensorflow Serving pt 1)
Tensorflow Serving pt 2
Tensorflow Lite (TFLite)
Why is Google the King of Distributed Computing?
Training with Distributed Strategies
Using the TPU
4 Topics
Differences Between Tensorflow 1.x and Tensorflow 2.x
Constants and Basic Computation
Variables and Gradient Tape
Build Your Own Custom Model
3 Topics
Mean Squared Error
Binary Cross Entropy
Categorical Cross Entropy
6 Topics
Gradient Descent
Stochastic Gradient Descent
Momentum
Variable and Adaptive Learning Rates
Adam (pt 1)
Adam (pt 2)
1 Topic
How to get the Tensorflow Developer Certificate
2 Topics
How to Choose Hyperparameters
Get the Exercise Pack for This Course
4 Topics
Pre-Installation Check
How to install Numpy Scipy Matplotlib Pandas IPython Theano and TensorFlow
Anaconda Environment Setup
Installing NVIDIA GPU-Accelerated Deep Learning Libraries on your Home Computer
6 Topics
How to use Github & Extra Coding Tips (Optional)
Beginner's Coding Tips
How to Code Yourself (part 1)
How to Code Yourself (part 2)
Proof that using Jupyter Notebook is the same as not using it
Is Theano Dead?
5 Topics
How to Succeed in this Course (Long Version)
Is this for Beginners or Experts? Academic or Practical? Fast or slow-paced?
Machine Learning and AI Prerequisite Roadmap (pt 1)
Machine Learning and AI Prerequisite Roadmap (pt 2)
Common Beginner Questions: What if I'm "advanced"?
2 Topics
What is the Appendix?
BONUS
Tensorflow 2.0: Deep Learning and Artificial Intelligence
Related Deep Learning Courses
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