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Learner Reviews & Feedback for Applied Machine Learning in Python by University of Michigan

4.6
stars
8,768 ratings

About the Course

This course will introduce the learner to applied machine learning, focusing more on the techniques and methods than on the statistics behind these methods. The course will start with a discussion of how machine learning is different than descriptive statistics, and introduce the scikit learn toolkit through a tutorial. The issue of dimensionality of data will be discussed, and the task of clustering data, as well as evaluating those clusters, will be tackled. Supervised approaches for creating predictive models will be described, and learners will be able to apply the scikit learn predictive modelling methods while understanding process issues related to data generalizability (e.g. cross validation, overfitting). The course will end with a look at more advanced techniques, such as building ensembles, and practical limitations of predictive models. By the end of this course, students will be able to identify the difference between a supervised (classification) and unsupervised (clustering) technique, identify which technique they need to apply for a particular dataset and need, engineer features to meet that need, and write python code to carry out an analysis. This course should be taken after Introduction to Data Science in Python and Applied Plotting, Charting & Data Representation in Python and before Applied Text Mining in Python and Applied Social Analysis in Python....

Top reviews

JL

Aug 19, 2018

Concise and clear presentation of the material with the majority of time focused around using TDD to learn and practice concepts through developing solutions to open ended coding challenges.

AG

Aug 26, 2017

A lot of techniques packed into a relatively short course. Weeks 2 & 4 are noticably tougher than the other two, so allow plenty of extra time for assignment and quiz in those 2 weeks.

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1126 - 1150 of 1,599 Reviews for Applied Machine Learning in Python

By ANGEL G M C

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Jul 11, 2021

great

By Shiyu M

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Oct 8, 2020

很有启发性

By Soumyajit M

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Oct 1, 2020

Great

By SHREYASHI D

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Sep 17, 2020

great

By Richard Z

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Sep 3, 2019

Good.

By Xia l

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May 16, 2019

GREAT

By xuhp

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Nov 12, 2018

great

By shubham s

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Mar 16, 2018

great

By Aradhaya S 2

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Jan 14, 2026

nice

By Abhaysing J M 2

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Jan 8, 2026

Good

By Deendayal K 2

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Dec 24, 2025

good

By Mayank Y 2

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Dec 23, 2025

okay

By Aditya S 2

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Dec 23, 2025

None

By Anshu K 2

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Dec 21, 2025

good

By divyanshu k

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Dec 13, 2025

Best

By Vritant J 2

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Nov 28, 2025

GOOD

By Sagnik P 2

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Nov 13, 2025

nice

By Anushka D 2

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Nov 11, 2025

good

By ahmed a s a z

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Mar 20, 2025

good

By SALONI C 2

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Dec 23, 2023

Good

By RAHUL O 2

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Jan 1, 2023

good

By Kunal J

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Mar 13, 2022

nice

By KAPATI V A

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Feb 8, 2022

nice

By Suman M

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Jan 25, 2022

good

By SURESH y

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Jan 13, 2022

good