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

4.6
stars
8,605 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 18, 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 22, 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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1301 - 1325 of 1,570 Reviews for Applied Machine Learning in Python

By Alpan A

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Nov 26, 2019

Very good curriculum with a hands on project. However thera are some limitations with the platform with grading

By Am T (

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Jun 21, 2017

Complete course on supervised learning

Would be nice to cover PCA and unsupervised learning in the assignments

By Andres V

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Oct 16, 2020

the final assignment was too hard compared to the other assignments and the contens given in the last module

By CMC

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Feb 9, 2019

A little dated. Overall a good introduction. The informal explanation of SVM was particularly effective.

By PDSS L K

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Sep 4, 2020

course is very informative with hands on details, assignments and quizzes are very useful for assessment

By Maxim P

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Sep 15, 2018

Nice there could just be a bit more of a case study to see the difference and decision ways in practices

By Jesús P

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Jan 5, 2018

great course but could be improved with a better explaining of the class on board for abstract concepts.

By shashank m

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Jul 16, 2019

Very intuitive course...and carefully designed so that it does not overwhelm the students with details

By ZHAI L

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May 10, 2018

Compared to previous two courses in this specialization, this course need more time for self-learning.

By Justin M

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Apr 10, 2018

Great course overall. Only reason for 4 stars is some of the assignments could use a bit more clarity.

By Manjeet K

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Sep 14, 2019

Easy to learn the course, just be focussed. Its an applied ML course, not to expect any mathematics.

By Marcela

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Oct 25, 2024

Challenging, but rewarding. I am glad I finished it. Thanks!! I really feel I learned a new skill.

By Ulka K

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Feb 27, 2020

I found the dataset in the last assignment difficult to interprit. I was hoping for a simpler one.

By Vishwa M

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Sep 3, 2021

Course Content was excellent. I really learned a lot. Assignment 4 was a hassle to submit though.

By Stephen R

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May 8, 2018

Wish there were a little more theory, realize it's an "Applied" course but still seemed lacking

By J N

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May 22, 2021

Teaching by the professor is very good and i learnt every thing from scratch thankyou coursera

By Pierre D

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May 1, 2021

Interesting course. Last exercise allows understanding how to use ML, when you are all alone.

By Michel H

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Jan 23, 2020

helpfull, but so many information in little time. Difficult to get clarified the ideas behind

By Samantha

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Apr 5, 2020

Very great courses ! It helps to deepen my knowledge in Machine learning. Very recommend it!

By Koffi K (

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Oct 14, 2019

A part from some small issues when doing the last assignment(4), Everything was all right.

By Nicholas P

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Dec 29, 2020

Good content and teacher but needs more interactivity before the final project every week

By WhiteCR

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Feb 15, 2020

Good course for practicing machine learning algorithms with Python Sci-kit Learn package.

By soymilk

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Oct 2, 2020

Contents of lecture are good but the assignments got many problems that should be fixed

By Falak S

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Oct 28, 2020

It's really a great course for the beginner to begin with the machine learning basics.