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Master Deep Learning and Neural Networks from Scratch

Introduction

What are Neural Networks

Types and Applications of Neural Networks

Supervised Learning
Why is deep learning getting popular now?

Neural Networks Basics

Binary Classification
Logistic Regression
Logistic Regression Cost Function
Gradient Descent Algorithm
Derivatives - part 1
Derivatives - part 2
Derivatives - part 3 (Sum Rule)
Derivatives - part 4 (Derivative of exponential function)
Derivatives - part 5 (Product Rule)
Derivatives - part 6 (Quotient Rule)
Computation Graph
Derivatives with Computation Graph - Backpropagation
Logistic Regression Gradient Descent
Gradient Descent on m Examples

Vectorization

Vectorization
More Vectorization examples using NumPy
Vectorizing Logistic regression Forward Propagation
Vectorizing Logistic regression Backpropagation

NumPy Quickstart Guide

NumPy - Overview
Creating NumPy arrays
linspace(), zeros() and ones()
Indexing Arrays
Slicing NumPy Arrays
Broadcasting NumPy Arrays

Shallow Neural Networks

One Hidden Layer Neural Network
Neural Network Representation
Neural Network Computation
Vectorizing computations across training examples
Activation Functions

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