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

4.6
stars
8,462 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

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.

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!!

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1476 - 1500 of 1,539 Reviews for Applied Machine Learning in Python

By Halil K

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Sep 26, 2019

Good content, bad teachng staff. Though the discussion forum contributors were very helpful and should be commended for their efforts.

By Ricardo R C

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Oct 23, 2021

I do not like this course, it has errors to be fixed, and the notebooks are not updated. Hope that in the future they can improve it

By Om R

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Apr 26, 2020

The course is great, but need certain improvement for assignments and quizzes. The facts should be checked multiple times.

By Darshan S

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Dec 31, 2019

Not enough real life examples throughout the video, makes it very hard to concentrate during the whole lecture.

By Mauricio A E G M

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Nov 17, 2019

This course is not useful to learn from scratch, but has some good things, for example the final assignment.

By Nikola G

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Jan 14, 2019

Really didn't like the quiz parts of the course. If it was up to me I would do thorough revision of these.

By Chirag S

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May 24, 2020

The content was less informative and audio quality was poor. However, assignments are fun completing.

By Rohit S

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May 21, 2020

The online grader needs to be updated as there is constant error showing up though our code is right

By Gilad A

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Jun 27, 2017

The last assignment was super. apart for it, the assignments and the course were too easy

By Sai P

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Jun 3, 2020

There were a few corrections made during the videos which ended being quite confusing.

By Philip L

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Oct 30, 2017

The assignments are extremely difficult, professor is a bit dry during lectures.

By Francesco C

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Feb 6, 2023

The course is very interesting but I found too many errors in the assignments.

By Dileep K

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Oct 3, 2021

Although content is really helpful, assignment part has many technical issues!

By Sundeep S S

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Apr 4, 2021

Only classification based ML is covered. Regression based ML is non-existant.

By Iuri A N d A

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Aug 4, 2021

It has potential, but the assignment evaluation had a lot to be fixed.

By Pakin P

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Jan 10, 2020

How can i pass without reading discuss about problem with notebook

By Hao W

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Aug 27, 2017

The homework is too easy to improve our understanding of ML

By M S V V

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Jun 29, 2020

Too much of information compressed within a short span.

By José D A M

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Jun 21, 2020

Too fast, yet too difficult. Needs deeper explanation.

By Navoneel C

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Nov 21, 2017

Nice and Informative but not practically effective

By Priyanka v

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May 8, 2020

if it is more detailedthen it will be more useful

By Numan A S

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Jan 8, 2024

update week 3 assignment. no clear instruction

By Sameed K

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Mar 15, 2018

have to figure out a lot of things on you own.

By Andy S

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Jun 4, 2019

It could have been better with more examples.

By Syed S

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Apr 12, 2020

The explanation could have been much better.