Course Content
Getting Started
Introduction to Deep Learning
Set-Up
Setting up an Integrated Development Environment (IDE)
Introduction to Neural Networks
The Single Input Single Output Neural Network
Coding: Single Input Single Output Neural Network
The Single Input Multiple Output Neural Network
Coding: Single Input Multiple Output Neural Network
The Multiple Input Single Output Neural Network
Coding: Multiple Input Single Output Neural Network
The Multiple Input Multiple Output Neural Network
Coding: Multiple Input Multiple Output Neural Network
The Hidden Layer Neural Network
Coding: The Hidden Layer Neural Network
Comparing and Finding Error
Coding: Finding Error
Understanding data representation in Machine Learning
Understanding the “Learning” in Machine Learning
Coding: Brute-force Learning
Introduction to Gradient Descent
Functional Description of a Biological Neuron
Case Study: Building a Neural Network to Predict Muscle Gain
Coding: Normalizing Datasets
Coding: Random Initialization of Weights
Understanding Activation Functions
Coding: Forward Propagation
Basics of Calculus
Logistic Regression
Case Study: Building a Neural Network to Detect Cats
Deep Neural Networks
Internals of a 2-layer Neural Network
Understanding Computational Graphs
Updating Parameters Effectively
Understanding the Importance of Vectorization
Summary of Back-propagation and Forward-propagation
Initializing Parameters Effectively
Understanding Layers and Units
Understanding the Shapes
Understanding Broadcasting in Programming
Improving Neural Networks with Regularization Techniques
Overfitting and Underfitting
Building a Complete Neural Network Library for Predicting Handwritten Numbers
Coding: Defining our Neural Network Structure
Building Our Neural Network Library Utility Functions
Coding: Defining our Data Object Structure
Coding: Implementing a Function to Read Data From a File
Coding: Implementing a Function to Parse our Data
Coding: Implementing more Utility Functions
Building Our Neural Network Library Engine
Coding: Implementing the Forward Propagation Function
Coding: Implementing the Back Propagation Function
Testing our Neural Network Library
Coding: Training a Model to Predict Handwritten Digits
Coding: Testing our Model
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