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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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1376 - 1400 of 1,562 Reviews for Applied Machine Learning in Python

By Catherine M

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Mar 1, 2021

Nice course. A lot of ML models get presented.

By harsh a

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Feb 3, 2018

Good course.

Thanks to entire team

Harsh Arora.

By Tianyu Z

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Jun 19, 2019

Some concepts should be introduced in detail.

By Ujjwal O

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Jul 5, 2023

more visual explanations would be better!!!!

By Amita A D

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May 18, 2018

Need more information about more algorithms

By CHAPPIDI S N B

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Jan 16, 2022

Excellent way of teaching and learned well

By Souvik M

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Jan 23, 2022

where is my certificate?????????????????

By Ruben W

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Sep 8, 2019

Best course so far in this specialisation

By Alan F

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Feb 28, 2018

Good course but there's a lot of material

By Abdulwaheed M

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Jun 17, 2020

Teaching is very good and it is helpfull

By Alperen B O

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Dec 16, 2020

I get late feedback for lab assignments

By Ramya K

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Jul 15, 2019

Well-organized but assignments too easy

By Supratim D

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Aug 10, 2017

Very informative but bit too difficult.

By ROHIT J

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Aug 2, 2020

very helpfull.thanks for creating this

By Xiang C

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May 12, 2020

It's good to learn how to use sklearn.

By Jagadish C A

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Sep 19, 2019

Gives good overview of ML using Pyton

By Mehrdad A

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Sep 22, 2024

It was summerized and beneficial

By Shreekant G

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Jul 17, 2019

Really taught best ML algorithms

By xingkong

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Aug 9, 2017

quiz is harder than assignment.

By Rainer S

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Feb 4, 2024

A tough but well worth class.

By shreyash t

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Jul 28, 2020

overalll good way to start ml

By Vaibhav S

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May 27, 2020

way better than last teacher.

By Nicolas B

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Jul 5, 2017

Muy buen curso, muy completo.

By Sanskriti G

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Oct 26, 2021

it was an amazing experience

By 李祥泰

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Aug 15, 2017

Nice courses with nice quiz!