A Friendly Introduction to Machine Learning

A friendly introduction to the main algorithms of Machine Learning with examples.
No previous knowledge required.

0:05 What is Machine Learning? Humans learn from past experiences, computers learn from previous data.
2:25 Linear Regression: Finding the line that works best between a given set of points.
4:10 Gradient Descent : Square of error minimization to get best line fit
6:20 Detecting Spam e-mails with Naive Bayes Algorithm
10:35 Decision Tree
13:20 Logistic Regression
17:00 Neural network as a logistic regression set intersection
18:50 Support Vector Machine with linear optimization
20:05 Kernel trick: planes for curves and vice-versa
26:00 K-Means clustering
28:30 Hierarchical Clustering
29:40 Summary
(Thanks to Nick Kartha for breaking down the topics!)

If you like this, there’s an extended version in this playlist:
https://www.youtube.com/playlist?list=PLAwxTw4SYaPknYBrOQx6UCyq67kprqXe3

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