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

4.6
stars
8,724 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

MB

Jun 19, 2017

Not for the faint of heart and some experience with Python, in particular Pandas, is preferred. Great overview of the different methods used in machine learning. One of the better courses imo.

DB

Oct 23, 2020

EXTREMELY USEFUL AND GOOD COURSE, CONGRATULATIONS TO ALL THE PEOPLE INVOLVE.Honestly, I never thought I could learn so much in an online course, excited for the rest of the specialization

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826 - 850 of 1,592 Reviews for Applied Machine Learning in Python

By Armand L

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Apr 25, 2018

Very Good Course ! learned a lot !

By Oleg D

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Mar 25, 2018

ONE OF THE BEST THAT ONE CAN FIND!

By Ariel F

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Oct 5, 2022

A very great and concise course!

By Cezariusz P

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Aug 12, 2022

Good materials but not easy exams

By Prajay Y

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Jan 12, 2022

Excellent well structured course

By Natalia D P

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Nov 5, 2021

LITLE BIT HARD BUT THE UI IS GOOD

By BIBI I 2

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Oct 31, 2021

Great course. Keep it up coursera

By NITHISH K

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Oct 12, 2020

Very excellent information gained

By Deekshith N

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Jul 22, 2020

Very good and interesting course.

By Chanaka S

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Jul 21, 2020

The hardest assigment i ever done

By Ovi S

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May 5, 2020

Awesome for intermediate learners

By Himanshu R

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Apr 28, 2020

It was great learning experience.

By Xiaoming Z

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Jan 12, 2019

Very informative, useful practice

By Hemalatha N

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Oct 25, 2017

Very informative & highly useful.

By Fernanda R L

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Oct 9, 2017

Very good, beyond my expectations

By Eunjae M J

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Jul 2, 2017

It was really hard, but worth it!

By Deni M

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May 30, 2021

Great course highly recommended

By Dinith M

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Nov 19, 2020

Learned a lot, excellent content

By Gaurav R

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Oct 22, 2020

best course for machine learning

By Saurabh D

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May 24, 2020

Very hands on. I learnt so much.

By Priscila L

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Nov 11, 2018

nice teacher, interesting course

By Sayan G

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Jun 15, 2018

Exhaustive and in depth coverage

By Guido L

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Feb 8, 2018

Very good, comprehensive course!

By Mwenimpako P S

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Jul 31, 2017

Very informative and educational

By José L

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Jun 6, 2017

Excellent material and tutoring!