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

4.6
stars
8,769 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

SA

Aug 14, 2019

- more technical materials, comparisons and better classified details should've been provided, especially to be more proportional to the assignments.-again, subtitles were full of typos

RS

Jun 9, 2020

The course was really interesting to go through. All the related assignments whether be Quizzes or the Hands-On really test the knowledge. Kudos to the mentor for teaching us in in such a lucid way.

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826 - 850 of 1,599 Reviews for Applied Machine Learning in Python

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!

By Ariel F

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Oct 5, 2022

A very great and concise course!

By Cezariusz P

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Aug 11, 2022

Good materials but not easy exams

By Prajay Y

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Jan 11, 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 11, 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 4, 2020

Awesome for intermediate learners

By Himanshu R

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Apr 27, 2020

It was great learning experience.

By Xiaoming Z

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Jan 11, 2019

Very informative, useful practice

By Hemalatha N

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Oct 24, 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 1, 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 21, 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 10, 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