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

4.6
stars
7,352 ratings
1,343 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!!

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

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651 - 675 of 1,320 Reviews for Applied Machine Learning in Python

By Muhammad F A

Jan 1, 2021

thanks for knowledge and live to inspire,peace

By Ana K A d M

Feb 7, 2020

Excellent balance between theory and practice!

By Krishna P S

Mar 1, 2018

Excellent course. Nicely designed & delivered.

By Eray Ö

Sep 26, 2017

great course with a lot of hands-on experience

By Mohammad Q M A

Jul 13, 2020

It is A great course ! I recommend to take it

By Punam P

Apr 15, 2020

Very Nice Course..I really Enjoyed it..Thanks

By Yongqing H

Aug 5, 2019

It's so hard. But every endless trying worth.

By Dario M

Jul 12, 2019

So far the best course in this specialization

By Rohit M S

Mar 22, 2019

The Course is amazing. you get to learn a lot

By Xiaoyue Z

Jul 30, 2018

A very helpful and confidence-building class!

By Ruyang L

Apr 20, 2018

Very interesting course, enjoyed it very much

By zios s

Nov 23, 2017

great course very useful in data science job.

By Om P

May 17, 2020

perfect for beginners! thank you, professor!

By Pilar V

Sep 14, 2019

Super interesting course and specialization!

By Joan P

Nov 5, 2017

Very interesting last programming assignment

By David M

Jul 7, 2017

Great introduction to Scikit-learn tool set.

By Danish R

Jul 2, 2017

P.S.: This is not an easy course to complete

By roberto T

Aug 17, 2020

Good course, especially on the applied side

By Ranjit K

Jul 26, 2020

Great Learning with good examples and tasks

By Olivier R

Jul 1, 2020

Highly Recommended, the Instructor is great

By 刘宇轩

Dec 14, 2017

The last homework is great and interesting.

By Thodoris N P

Oct 26, 2017

Most complete Machine learning course ever.

By MIFTAHUL J

Nov 30, 2020

very organized and helpful course. Thanks!

By Anurag B

Jun 8, 2019

Great Content, Great Delivery, Thumbs Up!!

By Darío A

Jun 2, 2018

Excellent course to get into sci kit leran