every blog needs subheader text Neural Networks and Deep Learning

Table of contents.

It had been a while since I finished Udacity's Deep Learning course, so as a refresher I signed up for Andrew NG's course.

These are my notes for the first course in the series: Neural Networks and Deep Learning.

Course Resources

Week 1: Introduction

A basic NN looks at housing price prediction, can use simple regression

Supervised learning maps Input(x) → Output(y)

Geoffrey Hinton Interview:

Hinton is fascinating and explains things really clearly.

Week 2: Basics of NN programming

First up, we do a binary classification via logistic regression, where we classify an image into 1 cat or 0 not cat. Key concepts for this:

Pieter Abbeel Interview:

Week 3: Code a simple NN

Ian Goodfellow interview:

Week 4: Code a deep NN

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