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Learner Reviews & Feedback for Machine Learning with Python by IBM

4.7
stars
16,540 ratings

About the Course

Get ready to dive into the world of Machine Learning (ML) by using Python! This course is for you whether you want to advance your Data Science career or get started in Machine Learning and Deep Learning. This course will begin with a gentle introduction to Machine Learning and what it is, with topics like supervised vs unsupervised learning, linear & non-linear regression, simple regression and more. You will then dive into classification techniques using different classification algorithms, namely K-Nearest Neighbors (KNN), decision trees, and Logistic Regression. You’ll also learn about the importance and different types of clustering such as k-means, hierarchical clustering, and DBSCAN. With all the many concepts you will learn, a big emphasis will be placed on hands-on learning. You will work with Python libraries like SciPy and scikit-learn and apply your knowledge through labs. In the final project you will demonstrate your skills by building, evaluating and comparing several Machine Learning models using different algorithms. By the end of this course, you will have job ready skills to add to your resume and a certificate in machine learning to prove your competency....

Top reviews

FO

Oct 8, 2020

I'm extremely excited with what I have learnt so far. As a newbie in Machine Learning, the exposure gained will serve as the much needed foundation to delve into its application to real life problems.

RC

Feb 6, 2019

The course was highly informative and very well presented. It was very easier to follow. Many complicated concepts were clearly explained. It improved my confidence with respect to programming skills.

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2351 - 2375 of 2,877 Reviews for Machine Learning with Python

By Dorjee G

•

Nov 11, 2019

Great course, great instructor. I enjoyed doing the Lab works.

Thanks,

By Mahendra S

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Jul 21, 2019

Contents are very useful and informative. A good start for beginners.

By Mujeebullah Y

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Oct 23, 2019

Good course. However, they need to explain the code more in details.

By Subhara S

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Oct 26, 2022

This was a very good course who are want to learn the basics from.

By Danny R

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Jan 30, 2024

Decent theoretical intro to machine learning but not much practice

By Alexandre N

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Dec 21, 2020

Recommendation systems could receive a peer-reviewed task as well.

By Hemanth A

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Jul 6, 2020

A good platform for users curious about the various ML techniques.

By Dhruv V C

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May 10, 2020

Marks were deducted for no reason in the peer graded assignment .

By Alexios M

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Mar 13, 2021

Well-structured course. It drives you stop-by-step in most cases.

By Harish K

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Jul 1, 2023

This course is very useful and also helps to improve your skills

By Nitai S

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Dec 8, 2021

notebook setups for final projects could have been much better.

By mohd z

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Jun 22, 2021

Awesome course with excellent content and Project based learning

By Ayushman S

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Apr 6, 2020

Some concepts were hurried. But jypyter notebooks are very good.

By Felicia C

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Dec 7, 2024

overall good, but I'd prefer more coding practice in python lab

By Abhinav K

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Mar 2, 2019

A complete package for those who want to start from the stratch

By Tao W

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Dec 31, 2023

- well structured content - I like jupyter lab, fun to try out

By Tien C B

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Jan 4, 2023

There are a few misleading and vague questions in the content.

By Amlan G

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Jul 21, 2022

This is a very gd course for a student to learn ML with python

By Subash L

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Jun 26, 2021

Over all good. The lab results could be explained a bit better

By KOSHAL K

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Feb 11, 2020

It is best for beginners for introduction to machine learning.

By Prakash R

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Feb 10, 2019

This course helps me to get understand about Machine Learning.

By Mohamed K

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Nov 19, 2024

pythopn coding execices should be graded at my point of view

By Germán G

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Apr 27, 2022

It is a good course, they could put more practical exercises.

By Ashis G

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Jun 27, 2020

A little more hands on training on the videos were necessary.

By Nicolas D I A

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Apr 14, 2023

It would be better to update the python code in each example