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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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701 - 725 of 1,320 Reviews for Applied Machine Learning in Python

By Marion T

May 31, 2019

good introduction to machine learning

By Michael T

Feb 21, 2019

Great content and reference materials

By BITATA G

Aug 26, 2020

great course with very good content!

By Tanishka M

Jul 13, 2020

Great course to master fundamentals!

By A. Z M R

Jun 8, 2019

The auto grader should be error free

By Mostafa H N Y

Jun 1, 2019

Very useful course. Thank you Kevyn.

By Dingqiang Y

Mar 22, 2019

Good introduction with python tools.

By Marcin C

Apr 29, 2018

Heavy, but extremely valuable course

By Guneet B

Apr 2, 2018

High Quality resources and materials

By Vladimír L

Jan 18, 2018

great course with a high value added

By Dheeraj P

Aug 24, 2017

nice lecture series, Good Approach .

By Yan

Jul 5, 2017

100% Free course as audit, recommend

By Javad K

Mar 24, 2021

This course was very useful for me.

By David W

Jan 12, 2020

A good introduction to Scikit learn

By Navid A E

Oct 16, 2018

Absolutely the best professor ever!

By Darren

Jul 2, 2017

Very Impressive and illustrative !!

By Catherine L

May 16, 2020

Excellent course. I learned A Lot.

By RICARDO D

Dec 3, 2019

Excellent material for intro to ML

By Daniel H

Jan 4, 2019

Kevyn Collins-Thompson is a legend

By Syam P N

Dec 17, 2018

Excellent course. Was very helpful

By Sudhir T

Aug 1, 2018

nice course and easy to understand

By Armand L

Apr 24, 2018

Very Good Course ! learned a lot !

By Oleg D

Mar 24, 2018

ONE OF THE BEST THAT ONE CAN FIND!

By NITHISH K

Oct 11, 2020

Very excellent information gained

By Deekshith N

Jul 22, 2020

Very good and interesting course.