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SVM Outlier Practice Intro to Machine Learning

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Lessons List | 494 Lesson
Introduction
00:02:39

Introduction
Introduction Part II
00:01:09

Introduction Part II
Introduction Pt III
00:00:46

Introduction Pt III
Prerequisites
00:00:58

Prerequisites
Machine Learning in the Google Self Driving Car
00:02:13

Machine Learning in the Google Self Driving Car
Quiz Intro to Machine Learning
00:01:40

Quiz Intro to Machine Learning
Solution Intro to Machine Learning
00:01:07

Solution Intro to Machine Learning
Supervised Classification Example Quiz Intro to Machine Learning
00:00:45

Supervised Classification Example Quiz Intro to Machine Learning
Supervised Classification Example Intro to Machine Learning
00:01:08

Supervised Classification Example Intro to Machine Learning
Features and Labels Musical Example
00:01:08

Features and Labels Musical Example
Features Visualization Quiz Intro to Machine Learning
00:01:04

Features Visualization Quiz Intro to Machine Learning
Features Visualization Solution Intro to Machine Learning
00:00:11

Features Visualization Solution Intro to Machine Learning
Classification By Eye Quiz Intro to Machine Learning
00:00:26

Classification By Eye Quiz Intro to Machine Learning
Classification By Eye Solution Intro to Machine Learning
00:00:31

Classification By Eye Solution Intro to Machine Learning
Intro To Stanley Terrain Classification
00:00:45

Intro To Stanley Terrain Classification
Speed Scatterplot Grade and Bumpiness Intro to Machine Learning
00:01:28

Speed Scatterplot Grade and Bumpiness Intro to Machine Learning
Speed Scatterplot Grade and Bumpiness Intro to Machine Learning
00:00:05

Speed Scatterplot Grade and Bumpiness Intro to Machine Learning
Speed Scatterplot 2 Intro to Machine Learning
00:00:06

Speed Scatterplot 2 Intro to Machine Learning
Speed Scatterplot 2 Intro to Machine Learning
00:00:09

Speed Scatterplot 2 Intro to Machine Learning
Speed Scatterplot 3 Intro to Machine Learning
00:00:07

Speed Scatterplot 3 Intro to Machine Learning
Speed Scatterplot 3 Intro to Machine Learning
00:00:35

Speed Scatterplot 3 Intro to Machine Learning
Scatterplots to Predictions Intro to Machine Learning
00:00:34

Scatterplots to Predictions Intro to Machine Learning
Scatterplots to Predictions Intro to Machine Learning
00:00:08

Scatterplots to Predictions Intro to Machine Learning
Scatterplots to Predictions 2 Intro to Machine Learning
00:00:10

Scatterplots to Predictions 2 Intro to Machine Learning
Scatterplots to Predictions 2 Intro to Machine Learning
00:00:11

Scatterplots to Predictions 2 Intro to Machine Learning
Scatterplots to Decision Surface Intro to Machine Learning
00:00:33

Scatterplots to Decision Surface Intro to Machine Learning
Scatterplot to Decision Surface Intro to Machine Learning
00:00:21

Scatterplot to Decision Surface Intro to Machine Learning
Good Linear Decision Surface Intro to Machine Learning
00:00:17

Good Linear Decision Surface Intro to Machine Learning
Good Linear Decision Surface Intro to Machine Learning
00:00:48

Good Linear Decision Surface Intro to Machine Learning
Transition to Using Naive Bayes
00:00:18

Transition to Using Naive Bayes
NB Decision Boundary in Python
00:00:38

NB Decision Boundary in Python
Getting Started With sklearn
00:01:26

Getting Started With sklearn
Gaussian NB Example
00:03:03

Gaussian NB Example
GaussianNB Deployment on Terrain Data Intro to Machine Learning
00:00:57

GaussianNB Deployment on Terrain Data Intro to Machine Learning
Gaussian Deployment Solution Intro to Machine Learning
00:00:13

Gaussian Deployment Solution Intro to Machine Learning
Accuracy of Naive Bayes Intro to Machine Learning
00:01:24

Accuracy of Naive Bayes Intro to Machine Learning
Accuracy of Naive Bayes Intro to Machine Learning
00:00:45

Accuracy of Naive Bayes Intro to Machine Learning
Training and Testing Data
00:01:13

Training and Testing Data
Unpacking NB Using Bayes Rule
00:00:21

Unpacking NB Using Bayes Rule
Bayes Rule
00:00:27

Bayes Rule
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Course Description

machine learning, in artificial intelligence (a subject within computer science), discipline concerned with the implementation of computer software that can .
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