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

4.6
stars
8,476 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

MB

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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.

SA

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- more technical materials, comparisons and better classified details should've been provided, especially to be more proportional to the assignments.

-again, subtitles were full of typos

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701 - 725 of 1,545 Reviews for Applied Machine Learning in Python

By Tue V

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Mar 25, 2020

I have learnt a lot from this course. Thanks so much

By Joshua A

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Dec 3, 2019

An excellent overview of Machine Learning in Python.

By Jose A P L

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Mar 16, 2019

Muy buen curso para iniciarse en el machine learning

By Dibyendu C

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Oct 17, 2018

Well structured and quality lectures and assignments

By Anthony K

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Jul 5, 2017

So far the course is relevant and very approachable.

By Aniket K S

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Aug 25, 2020

Give a lot idea about implementing machine Learning

By Haozhe ( X

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May 31, 2020

Great course. Love the design for each assignments.

By Archunan G

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Dec 3, 2019

Course is interesting and nice . quiz made well .

By MAINAK C

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Aug 20, 2019

very nice and apt course for all types of learners.

By Lutz H

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Jun 17, 2019

Really well explained. Great excersices! Well done!

By Aman K

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Mar 6, 2019

Course Material is quite interesting and practical.

By Mai N

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Sep 8, 2018

Good starting points for any machine learning folks

By Ebenezer A W

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Nov 14, 2017

A really nice course to begin machine learning with

By LEE D D

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Nov 9, 2017

Perfect and hard course than Andrew Ng's ML course!

By A A

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Aug 4, 2017

Best introduction to sklearn library I came across!

By zhang y

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Oct 3, 2021

comprehensive machine learning course for beginner

By Pratama A A

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Jul 14, 2020

If you're beginner i suggest dont take this course

By Ameya B

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Jul 3, 2020

Overall good intro to actually using scikit-learn.

By likejian

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May 14, 2020

It’s very nice course to learn ML for the new guys

By Abdelrahman M s A

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Feb 26, 2018

One of the best practical ML courses in the field!

By ARUN S

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Nov 9, 2017

Great professor with lot of real world experience.

By ChanLung

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Jul 31, 2017

Excellent Machine Learning Course for application!

By Rui J (

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Nov 16, 2021

it is so much fun to write programms on your own!

By Oxana M

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Dec 7, 2020

I like this cource. It gives a very good overview

By Bauyrzhan A

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Nov 15, 2020

It is decent course with fair level of complexity