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

4.6
stars
8,587 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

BS

Sep 17, 2020

Great content and good instruction. Need to fix the files in the assignments though. It's hard to keep track in the forums and frustrating go back and forth to find out why it's not working.

MB

Jun 18, 2017

Not for the faint of heart and some experience with Python, in particular Pandas, is preferred. Great overview of the different methods used in machine learning. One of the better courses imo.

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1076 - 1100 of 1,562 Reviews for Applied Machine Learning in Python

By Pratham N

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Aug 22, 2019

very good

By Edgar M d J G B

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May 13, 2019

Excelente

By Марчевский В Д

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Apr 29, 2019

Good one!

By Parul S

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Mar 25, 2019

excellent

By Cyrus N A P

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Nov 24, 2018

THE BEST!

By Saumya S

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Sep 12, 2018

excellent

By timetraveller

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Sep 7, 2018

nice shiz

By Srilatha T

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Jan 9, 2018

excellent

By Arnab

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Nov 3, 2017

Excellent

By clark x

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Jul 2, 2017

very good

By Megha T

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Jun 26, 2017

helpful !

By Daniel C C

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Jun 22, 2017

Amazing!!

By Sourav P

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Jul 26, 2021

too good

By Oméro B P N

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Feb 2, 2021

Amazing!

By Shreyash

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Nov 30, 2020

Awesome!

By Arnab M

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Sep 22, 2020

Good one

By David B d M J

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Sep 2, 2020

awesome!

By RAUL G & F - L & R E

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Jun 9, 2024

AWESOME

By Shatha N

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Feb 25, 2022

Greate

By MANSURIYA R K 2

•

Oct 31, 2021

Superb-

By Mohammad Y

•

Jun 19, 2020

Perfect

By PRASANNA R

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Sep 24, 2019

awesome

By SHAHUL E

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Sep 30, 2018

awesome

By Ankur K

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Sep 13, 2018

Awesome

By Deleted A

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Jul 25, 2018

Awesome