目录
1
前言
1.1
介绍
2
教师讲解
2.1
01.Intro
2.2
02.Regression Intro
2.3
03.Regression Features and Labels
2.4
04.Regression Training and Testing
2.5
05.Regression forecasting and predicting
2.6
06.Pickling and Scaling
2.7
07.Regression How it Works
2.8
08.How to program the Best Fit Slope
2.9
09.How to program the Best Fit Line
2.10
10.R Squared Theory
2.11
11.Programming R Squared
2.12
12.Testing Assumptions
2.13
13.Classification w_ K Nearest Neighbors Intro
2.14
14.K Nearest Neighbors Application
2.15
15.Euclidean Distance
2.16
16.Creating Our K Nearest Neighbors Algorithm
2.17
17.Writing our own K Nearest Neighbors in Code
2.18
18.Applying our K Nearest Neighbors Algorithm
2.19
19.Final thoughts on K Nearest Neighbors
2.20
20.Support Vector Machine Intro and Application
3
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2.6
06.Pickling and Scaling
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