Machine Learning Introduction

What’s the Machine Learning?

Humans learn from past experiences, Whereas computers need to be told what to do, they need to be programmed.

Teaching computers to learn to perform tasks from past experiences–previous data.

1. Decision Tree(Recommending Apps)
2. Naive Bayes Algorithm(Detecting Spam emails)
3. Gradient descent
4. Linear regression(predict house price)
5. Logistic regression(acceptance at a university)
6. Support vector machine
7. Kernel Trick
8. Neural Network
9. L&S&K&N
10. K-Means Clustering
11. Hierarchical Clustering

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Main Algorithm

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Decision Tree

Recommending Apps

Gender	Age	App
F	15	Pokemon Go
F	25	WhatsApp
M	32	Snapchat
F	40	WhatsApp
M	12	Pokemon Go
M	14	Pokemon Go

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Naive Bayes Algorithm

Detecting Spam emails

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Gradient descent

Look for the biggest downward direction

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Linear regression

Price of a house, the best fitting line

This general procedure to minimize the error, is know as gradient descent.

Least Squares

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Logistic regression

acceptance at a university

the log loss function, the error function

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Support vector machine

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Kernel Trick

it’s very well used in support vector machines.

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Neural Network

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L&S&K&N

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K-Means CLustering

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Hierarchical Clustering

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