AI News, Top 10 Machine Learning Videos on YouTube, updated

Top 10 Machine Learning Videos on YouTube, updated

YouTube contains a great many videos on the topic of Machine Learning, but it can be hard to figure out what's worth watching, especially since 300 hours of video are uploaded to YouTube every minute.

Here we bring you the most popular recent Machine Learning videos worth watching. This post updates a previous very popular post Top 10 Machine Learning Videos on YouTube from 2015.  We also added a few top relevant playlists. 

Machine Learning (Stanford) (1.4M views) This is the first video (Lecture 1 published 8 years ago) in the great series of Stanford machine learning lectures given by Andrew Ng.

(1.3M views) The video uploaded by ColdFusion (formally known as ColdfusTion) to show  “the cutting edge of the world around us in a fun relaxed atmosphere”;

(1.05M views) This animation lasts less than 3 minutes but illustrated automated design of motion strategy using genetic algorithm and neural network.

Originally developed by researchers and engineers working on the Google Brain Team within Google's Machine Intelligence research organization for the purposes of conducting machine learning and deep neural networks research.

1,281,106 views in total) These videos are part of an online course, Intro to Machine Learning.  This course was designed as part of a program to help you and others become a Data Analyst;

730,896 views) This course (CS229) -- taught by Professor Andrew Ng -- provides a broad introduction to machine learning and statistical pattern recognition.

Recent applications of machine learning, such as to robotic control, data mining, autonomous navigation, bioinformatics, speech recognition, and text and web data processing are also discussed.

Lecture 10 - Neural Networks

Neural Networks - A biologically inspired model. The efficient backpropagation learning algorithm. Hidden layers. Lecture 10 of 18 of Caltech's Machine ...

11. Introduction to Machine Learning

MIT 6.0002 Introduction to Computational Thinking and Data Science, Fall 2016 View the complete course: Instructor: Eric Grimson ..

Lecture 04 - Error and Noise

Error and Noise - The principled choice of error measures. What happens when the target we want to learn is noisy. Lecture 4 of 18 of Caltech's Machine ...

Lecture 1 | Machine Learning (Stanford)

Lecture by Professor Andrew Ng for Machine Learning (CS 229) in the Stanford Computer Science department. Professor Ng provides an overview of the course ...

Machine Learning & Artificial Intelligence: Crash Course Computer Science #34

So we've talked a lot in this series about how computers fetch and display data, but how do they make decisions on this data? From spam filters and self-driving ...

Lecture 03 -The Linear Model I

The Linear Model I - Linear classification and linear regression. Extending linear models through nonlinear transforms. Lecture 3 of 18 of Caltech's Machine ...

Lecture 01 - The Learning Problem

The Learning Problem - Introduction; supervised, unsupervised, and reinforcement learning. Components of the learning problem. Lecture 1 of 18 of Caltech's ...