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

4.6
stars
8,514 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

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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776 - 800 of 1,550 Reviews for Applied Machine Learning in Python

By Gustavo H d N

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Aug 31, 2019

Good balance between theory and practice.

By dan s

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Dec 30, 2017

Fantastic Course. I highly recommend it.

By Tinniam V G

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Sep 7, 2017

Terrific course. Many thanks to the Prof!

By Nguyen T S

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Nov 16, 2021

Thank you! this course is very helpful.

By Vaneeza I

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Aug 29, 2021

Highly recommended courses for beginners

By William H

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Sep 2, 2019

Excellent instructor and course material

By Patrick K

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Nov 22, 2018

Very nicely explained. Highly recommend.

By József V

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Apr 29, 2018

Broad range of ML knowledges is covered!

By hema m M

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Jun 30, 2020

Very helpful and interesting resources.

By Vishant J

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Apr 18, 2020

excellent course for beginners as well!

By Alexander G

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Jul 15, 2019

Nice course on machine learning basics!

By Nan L

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Jun 17, 2018

I think this course is difficult for me

By Ranjeetha V

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May 16, 2022

Excellent teacher and well explained!

By Henrique G A

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Jan 25, 2021

Best course with the best professor!!!

By Pavan M

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Jan 19, 2021

Course is Good and Very well presented

By Muhammad E

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Oct 26, 2020

very good course totally recommend it

By RAMISETTI B R

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Feb 7, 2020

wow!!!great feeling from learning here

By Mariano S C

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Oct 25, 2019

great course, excellent teaching staff

By Shadi A

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May 6, 2019

Best Instructor and simple explanation

By Nilesh I

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Oct 5, 2018

Practical, I liked the evaluation part

By SANKURU M K

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May 17, 2020

very nice course.usefull for beginers

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!