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

4.6
stars
7,138 ratings
1,295 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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1076 - 1100 of 1,274 Reviews for Applied Machine Learning in Python

By Wynona R N

Jun 23, 2020

Good introduction course on machine learning algorithms. The books and the readings are recommended to look through!

By Amanda V C

Jun 2, 2018

You will learn a lot. But the course is a little bit fast for regular students. Assignments deal with real problems.

By Rohith S

Nov 16, 2017

A few more code examples would have helped better understand various packages provided by Python and how to use them

By lcy9086

Feb 2, 2019

Great course on doing machine learning use sklearn and put little but enough explanation of the theories behind it!

By Alexandr S

Feb 24, 2019

It would be nice to have more practical assignments like the last one! Anyway it was very interesting! Thank you!

By Bharat G

Aug 30, 2017

Amazing Course but Please add some more theory and concepts in Neural Networking.Overall it is a good experience.

By Alpan A

Nov 27, 2019

Very good curriculum with a hands on project. However thera are some limitations with the platform with grading

By am

Jun 21, 2017

Complete course on supervised learning

Would be nice to cover PCA and unsupervised learning in the assignments

By Andres V

Oct 16, 2020

the final assignment was too hard compared to the other assignments and the contens given in the last module

By CMC

Feb 9, 2019

A little dated. Overall a good introduction. The informal explanation of SVM was particularly effective.

By divya p

Sep 4, 2020

course is very informative with hands on details, assignments and quizzes are very useful for assessment

By Maxim P

Sep 15, 2018

Nice there could just be a bit more of a case study to see the difference and decision ways in practices

By Jesús P S

Jan 5, 2018

great course but could be improved with a better explaining of the class on board for abstract concepts.

By shashank m

Jul 16, 2019

Very intuitive course...and carefully designed so that it does not overwhelm the students with details

By ZHAI L

May 11, 2018

Compared to previous two courses in this specialization, this course need more time for self-learning.

By Justin M

Apr 11, 2018

Great course overall. Only reason for 4 stars is some of the assignments could use a bit more clarity.

By Manjeet K

Sep 14, 2019

Easy to learn the course, just be focussed. Its an applied ML course, not to expect any mathematics.

By Ulka K

Feb 27, 2020

I found the dataset in the last assignment difficult to interprit. I was hoping for a simpler one.

By Stephen R

May 8, 2018

Wish there were a little more theory, realize it's an "Applied" course but still seemed lacking

By Michel H

Jan 23, 2020

helpfull, but so many information in little time. Difficult to get clarified the ideas behind

By Samantha

Apr 5, 2020

Very great courses ! It helps to deepen my knowledge in Machine learning. Very recommend it!

By Koffi M K

Oct 14, 2019

A part from some small issues when doing the last assignment(4), Everything was all right.

By Nicholas P

Dec 29, 2020

Good content and teacher but needs more interactivity before the final project every week

By WhiteCR

Feb 15, 2020

Good course for practicing machine learning algorithms with Python Sci-kit Learn package.

By Massimo T

Nov 12, 2019

The python packages used in the course are becoming outdated

adding useless difficulties.