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

4.6
stars
7,412 ratings
1,351 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

OA
Sep 8, 2017

This course is ideally designed for understanding, which tools you can use to do machine learning tasks in python. However, for deep understanding ML algorithms you should take more math based courses

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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576 - 600 of 1,331 Reviews for Applied Machine Learning in Python

By kuleafenu j

Jan 8, 2020

I have rely enjoyed this course because it is very informative

By poornanandasa

Aug 18, 2019

it was nice and everything was super and explanation was super

By Sudharshana B B

Jun 15, 2019

An excellent program on applied Machine and highly recommended

By Roberto L L

Jan 26, 2019

Awesome Course, I learned a lot of tools from Machine Learning

By Samuel E G G

Dec 16, 2018

Fantastic. Though the teacher is not as good as the first one.

By Luciano A D

Oct 18, 2020

Excellent course, and awesome teacher. He knows his stuff!!!!

By Fábio R D d B

Jan 17, 2019

Great course. Good mood to expose info. Congrats for content!

By Harshit K

Oct 4, 2017

One of the great courses to learn machine learning in Python.

By BENJAMÍN E V

Oct 11, 2020

Very complete course, great professor and a good assignments

By Mega D

Oct 15, 2019

Great class with very informative examples, and applicatoins

By ANURAG S

Sep 18, 2019

Course was fully explained in details and with good exercise

By Ayon B

Oct 19, 2018

Good course. And challenging indeed, especially the quizzes.

By Sathvik K

Aug 28, 2018

great for learning how to practically apply machine learning

By sunil s

Jul 5, 2018

Great course for implementing machine learning using python.

By Wai Y P S

Jun 22, 2021

Thanks you so much University of Michigan for Great course

By Fernando G

Mar 16, 2021

Excellent course! Well paced and you end up learning a lot!

By Hafiz A Q

May 18, 2020

A very nice course from the implementation point of view!!!

By Mikhailov R

Jan 27, 2019

Sometimes the lecturer is boring but overall perfect course

By Maciej W

Jul 8, 2018

Very informative, broad, hands-on course. Strong recommend.

By nitin p

Feb 28, 2018

Very Interesting and fascinating Course of Machine Learning

By Biju S

Oct 12, 2017

Very tough to finish. Big gap with material and assignments

By Amoghavarsha B

Mar 19, 2020

Perfect course with lots of assignments and good material!

By Yu S

Jul 16, 2018

Good applied material to study along theoretical material!

By Marek S

Sep 29, 2017

Useful, practical use of sklearn to machine learning tasks

By Matias B M

Aug 14, 2017

Challenging and rewarding. Wouldn't have it any other way.