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

4.6
stars
7,590 ratings
1,387 reviews

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

FL
Oct 13, 2017

Very well structured course, and very interesting too! Has made me want to pursue a career in machine learning. I originally just wanted to learn to program, without true goal, now I have one thanks!!

AS
Nov 26, 2020

great experience and learning lots of technique to apply on real world data, and get important and insightful information from raw data. motivated to proceed further in this domain and course as well.

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1226 - 1250 of 1,372 Reviews for Applied Machine Learning in Python

By harsh a

Feb 3, 2018

Good course.

Thanks to entire team

Harsh Arora.

By XJTLU

Jun 19, 2019

Some concepts should be introduced in detail.

By Amita D

May 18, 2018

Need more information about more algorithms

By Ruben W

Sep 8, 2019

Best course so far in this specialisation

By Alan F

Feb 28, 2018

Good course but there's a lot of material

By Abdulwaheed M

Jun 17, 2020

Teaching is very good and it is helpfull

By Alperen B O

Dec 16, 2020

I get late feedback for lab assignments

By Ramya K

Jul 15, 2019

Well-organized but assignments too easy

By Supratim D

Aug 10, 2017

Very informative but bit too difficult.

By ROHIT J

Aug 2, 2020

very helpfull.thanks for creating this

By Xiang C

May 12, 2020

It's good to learn how to use sklearn.

By Jagadish C A

Sep 19, 2019

Gives good overview of ML using Pyton

By Shreekant G

Jul 17, 2019

Really taught best ML algorithms

By xingkong

Aug 9, 2017

quiz is harder than assignment.

By shreyash t

Jul 28, 2020

overalll good way to start ml

By Vaibhav S

May 27, 2020

way better than last teacher.

By Nicolas B

Jul 5, 2017

Muy buen curso, muy completo.

By 李祥泰

Aug 15, 2017

Nice courses with nice quiz!

By 刘倬瑞

Jul 29, 2017

Useful, though a little easy

By Landon M L

Jul 9, 2017

the discussion forum is good

By Rizvaan M

May 21, 2020

This was a great course.

By Biswakarmi K

Aug 18, 2021

v​ery helpful course..

By Yassin B M

Jul 17, 2020

Good Course , Thanks!!

By Burak

Sep 30, 2018

good for scikitlearn.

By David P

Aug 4, 2021

A really good course