Neural Networks & Deep Learning

YouTube Tutorials

How Deep Neural Networks Work by Brandon Rohrer

https://www.youtube.com/watch?v=ILsA4nyG7I0

https://brohrer.github.io/how_neural_networks_work.html

A friendly introduction to Deep Learning and Neural Networks by Luis Serrano

https://www.youtube.com/watch?v=BR9h47Jtqyw

Visual Introduction to Neural Network by 3Blue1Brown

https://www.youtube.com/playlist?list=PLZHQObOWTQDNU6R1_67000Dx_ZCJB-3pi

Deep Learning Demystified

https://www.youtube.com/watch?v=Q9Z20HCPnww

http://brohrer.github.io/deep_learning_demystified.html

Courses

How Deep Neural Networks Work by Brandon Rohrer

A conceptual overview of neural networks, the workhorse of artificial intelligence https://end-to-end-machine-learning.teachable.com

Stanford Winter Quarter 2016 class: CS231n: Convolutional Neural Networks for Visual Recognition by Andrej Karpathy

https://www.youtube.com/playlist?list=PLkt2uSq6rBVctENoVBg1TpCC7OQi31AlC

Latest Course : http://cs231n.stanford.edu/

Machine Learning

A Friendly Introduction to Machine Learning by Luis Serrano

https://www.youtube.com/watch?v=IpGxLWOIZy4

This video explains

• What is Machine Learning? Humans learn from past experiences, computers learn from previous data.
• Linear Regression: Finding the line that works best between a given set of points.
• Gradient Descent : Square of error minimization to get best line fit
• Detecting Spam e-mails with Naive Bayes Algorithm
• Decision Tree
• Logistic Regression
• Neural network as a logistic regression set intersection
• Support Vector Machine with linear optimization
• Kernel trick: planes for curves and vice-versa
• K-Means clustering
• Hierarchical Clustering
• Summary

Machine Learning Cheatsheet

Brief visual explanations of machine learning concepts with diagrams, code examples and links to resources for learning more.

https://ml-cheatsheet.readthedocs.io/en/latest/