IBM

Machine Learning with Python

This course is part of multiple programs.

SAEED AGHABOZORGI
Joseph Santarcangelo

Instructors: SAEED AGHABOZORGI

491,044 already enrolled

Included with Coursera Plus

4.7

(16,540 reviews)

Intermediate level

Recommended experience

1 hour to complete
Flexible schedule
Learn at your own pace
94%
Most learners liked this course
4.7

(16,540 reviews)

Intermediate level

Recommended experience

1 hour to complete
Flexible schedule
Learn at your own pace
94%
Most learners liked this course

What you'll learn

  • Describe the various types of Machine Learning algorithms and when to use them 

  • Compare and contrast linear classification methods including multiclass prediction, support vector machines, and logistic regression 

  • Write Python code that implements various classification techniques including K-Nearest neighbors (KNN), decision trees, and regression trees 

  • Evaluate the results from simple linear, non-linear, and multiple regression on a data set using evaluation metrics 

Details to know

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Taught in English

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Learner reviews

4.7

16,540 reviews

  • 5 stars

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Showing 3 of 16540

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4

Reviewed on Dec 31, 2019

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Reviewed on Oct 8, 2020

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Reviewed on Jun 24, 2020

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