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

4.6
stars
8,585 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

S

Oct 23, 2021

It was good learning Machine Learning thru Python as using Python libraries like Pandas , Tensorflow,.etc made the work easier. Hope to do my masters in Machine Learning . Happy Learning <3

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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801 - 825 of 1,562 Reviews for Applied Machine Learning in Python

By Marion T

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May 31, 2019

good introduction to machine learning

By Michael T

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Feb 21, 2019

Great content and reference materials

By marco f

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Mar 9, 2022

One of the best I had with coursera

By BITATA G

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Aug 26, 2020

great course with very good content!

By Tanishka M

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Jul 13, 2020

Great course to master fundamentals!

By A. Z M R

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Jun 8, 2019

The auto grader should be error free

By Mostafa H

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Jun 1, 2019

Very useful course. Thank you Kevyn.

By Dingqiang Y

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Mar 22, 2019

Good introduction with python tools.

By Marcin C

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Apr 29, 2018

Heavy, but extremely valuable course

By Guneet B

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Apr 2, 2018

High Quality resources and materials

By Vladimír L

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Jan 18, 2018

great course with a high value added

By Dheeraj P

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Aug 24, 2017

nice lecture series, Good Approach .

By Yan

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Jul 5, 2017

100% Free course as audit, recommend

By Edward M

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Oct 4, 2021

Great content ,, Greater instructor

By Javad K

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Mar 24, 2021

This course was very useful for me.

By David W

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Jan 12, 2020

A good introduction to Scikit learn

By Navid A E

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Oct 16, 2018

Absolutely the best professor ever!

By Darren

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Jul 2, 2017

Very Impressive and illustrative !!

By Catherine L

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May 16, 2020

Excellent course. I learned A Lot.

By RICARDO D

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Dec 3, 2019

Excellent material for intro to ML

By Daniel H

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Jan 4, 2019

Kevyn Collins-Thompson is a legend

By Syam P N

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Dec 17, 2018

Excellent course. Was very helpful

By Sudhir T

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Aug 1, 2018

nice course and easy to understand

By Armand L

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Apr 24, 2018

Very Good Course ! learned a lot !

By Oleg D

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Mar 24, 2018

ONE OF THE BEST THAT ONE CAN FIND!