Chevron Left
Back to Applied Machine Learning in Python

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

4.6
stars
7,054 ratings
1,284 reviews

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

OA
Sep 8, 2017

This course is ideally designed for understanding, which tools you can use to do machine learning tasks in python. However, for deep understanding ML algorithms you should take more math based courses

AS
Nov 26, 2020

great experience and learning lots of technique to apply on real world data, and get important and insightful information from raw data. motivated to proceed further in this domain and course as well.

Filter by:

226 - 250 of 1,265 Reviews for Applied Machine Learning in Python

By shashank s

Aug 19, 2017

the content of videos , quiz and exercise all work extremely well together towards the stated goal of the course i.e. to give the learner a good over view of how to apply ML theories into action

By Michael B

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.

By Brett S

Sep 18, 2020

Great content and good instruction. Need to fix the files in the assignments though. It's hard to keep track in the forums and frustrating go back and forth to find out why it's not working.

By PRAKHAR K J

Apr 13, 2020

It feels good to learn something new and highly skilled demand in Engineering. Thanks to Coursera and instructor for providing such a wonderful opportunity of learning through your platform.

By Jens L

Aug 20, 2018

Concise and clear presentation of the material with the majority of time focused around using TDD to learn and practice concepts through developing solutions to open ended coding challenges.

By Amithabh S

Jun 23, 2017

Excellent course for someone who already has some knowledge of python but not quite familiar with machine learning. This course will teach you the application of machine learning in python.

By Abdirahman A A

Jan 13, 2019

In depth course that covers a lot in a short amount of time. If you take some extra time to delve deeper into these topics, you can ensure a great overview of machine learning with python.

By Diego A L B

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

By Indrajit P

Mar 29, 2020

Very well structured and informative course ! All the lectures are concise and give enough context for self-exploration. The assignments provide are a good hands-on experience as well !!

By jay s

Jul 15, 2017

Excellent lectures, good exercises to reinforce the material, and absolutely loved the explanations of the sophisticated mathematical models that made them more lucid and easy to digest.

By Keary P

Mar 24, 2019

Great for high level concepts and practical applications of machine learning. After taking this course I feel more confident in my ability to work on real world machine learning tasks.

By Andrew G

Aug 27, 2017

A lot of techniques packed into a relatively short course. Weeks 2 & 4 are noticably tougher than the other two, so allow plenty of extra time for assignment and quiz in those 2 weeks.

By Tian L

Apr 20, 2020

it is a great course that covers the most important basics of the "traditional" machine learning and helps me build a solid foundation for more advanced machine learning topics later.

By Alan H

May 8, 2019

Great course for the applications of machine learning. While I wouldn't recommend for someone with no ML experience, this was a great course for an R user trying to learn more python!

By Rami A T

Jun 6, 2017

Very helpful and well-structured course, clear lecturing, and high-level assignments. I hope, however, if it can be offered another course specialized in unsupervised learning in ML.

By RAQUIB S

May 5, 2020

Great Course. I love the way it is designed, delivered. I learned a lot. The most important part is that I enjoy every bit of the session and completed everything less than a week,

By Muhammad A

Jun 8, 2018

I am just about to begins my Module 2 but I have realized that how much easy to understand and to the point course is. I would love complete it and be the proud scientist. Thanks.

By Jesus P I

Apr 18, 2018

The most practical course I have completed so far. Also the right amount of theory needed to being able to start resolving your first machine learning problems. 100% recommendable

By Ravi M

Feb 8, 2020

Course was designed in a well structured manner and the basic concepts were covered for Regression and Classification. Many many thanks to University of Michigan for creating it.

By Gogul I

Jun 28, 2019

This is the best ever course I have taken in Coursera. Learnt very useful ML concepts that are no where available in the internet. Highly recommend this course to ML enthusiasts.

By Mohamed A H

Dec 15, 2018

Awesome course!

Stick till the end of it, and you'll never regret it.

You're gonna have a lot of fun especially in the last week, don't skip the optional readings of this week ;)

By Malvik P

Oct 30, 2019

The course is awesome. Professor Kevyn Collins Thompson, explains the topics with examples in python which makes content easy to understand. It is the best course for beginners.

By vishy d

Aug 6, 2017

It is very good blend of study and practical assignment. Assignments were very well designed to greatly enhance the understanding about the things learned in the video lectures.

By Juan D O V

Jun 15, 2020

Really good course, although it is more focused on the practical aspect I really learn much more about different machine learning techniques for improving and applying a model.

By Hanbin Z

Aug 20, 2019

It is a great course. The lectures is interesting and full of knowledge. Though the assignments are challenging, especially the last one, I really learn a lot from this course.