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

4.6
stars
6,734 ratings
1,212 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

FL

Oct 14, 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!!

OA

Sep 09, 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

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301 - 325 of 1,192 Reviews for Applied Machine Learning in Python

By Jose A P A

Jul 14, 2020

Un excelente curso para reforzar lo aprendido en el curso Minería de Datos para la Toma de Decisiones que se dicta en la Universidad Esan.

By Moustafa A S

Jul 28, 2020

GREAT COURSE!, this is one of the greatest courses for applying machine learning and data science algorithms and skills, great great job.

By Ritesh P N

Jul 19, 2020

It was amazing course for applied machine learning. The tutor was good teaching core concepts of machine learning algorithms step by step

By Sunny K L W

Sep 08, 2018

Great Course with high practicality. Need more lectures on how to process categorical data. Read the Forum if you encounter any question!

By Fengping W

Mar 28, 2018

It is really a good one, and I learn a lot here, both for theory and applied skills. And the reading materials are really good resources

By Shuyi Y

Jun 28, 2017

This course is great because I received so much training in applying the ML packages and functions python. A lot of hands-on experience!

By Marcelo P

Jul 09, 2019

Great course! Superb professor! Very well organized and structured. Lots of useful optional articles and videos. Learned a lot. Thanks!

By Nguyen K T

Jun 25, 2019

A very practical course and it helps me to understand more about machine learning theory. After all, this is a great course. Thank you.

By Mehmet F C

Dec 27, 2018

good one to quickly start learning ML - covering models, what they do, and how to tune them. Not going deep into the "how" models work.

By Shao Y ( H

Sep 08, 2017

Very good survey of all fundamental topics of machine learning! Good resources for preparation for technical data science interview! :)

By INHOI J

Apr 26, 2020

Great course. Professor delivered very complicated concepts of machine learning very easily. Quiz and assignments were very helpful.

By Keith M

Oct 12, 2020

Excellent course. Very detailed, very interesting, a lot to get through in each week. Lots of great examples of code and scenarios.

By Quan S

May 08, 2019

Course materials are very systematic and instructive, and the professor teaches very clearly. I like this course and recommend it.

By Flavia A

Mar 11, 2018

Practical class to learn well-known models and scikit-learn. The practice tests are great to help you move from theory to practice.

By Aniket S K

Jul 01, 2020

Good Course. Not for beginners starting with Machine Learning. Intermediate level. Prior knowledge of python libraries would help.

By Émile J

May 19, 2020

The exercices and evaluations are more complex than in the previous courses in this short program, but also much more instructive.

By Himanshu B

May 15, 2020

It was really an excellent well designed course, I gained valuable information that I will use as a business analytics in future.

By Ivan S F

Mar 23, 2019

Very good course. Not very deep, but definitively very wide and appropriate for an overview course of machine learning in python.

By abdulkader h

Jul 04, 2017

I appreciate so much this course even it was so dense and slitly short. It would be useful to extend it over several weeks again.

By usama i

Oct 12, 2020

Excellent course to understand and learn about how to work with available classifiers in scikit learn. Thanks for this course :)

By Ari W R

Aug 28, 2020

it is a pleasure to learn about machine learning course. I can remind and study again about the main things in machine learning.

By Jason L

Aug 26, 2020

Very solid course. Covers so many key machine learning concepts in a short period of time. Week 2 is intense - but awesome!

By Mahindra S R

Mar 28, 2020

Useful for understanding the application part of ML whereas Andrew Ng's course gives a more in-depth understanding of the topics

By SURENDRA O

Dec 25, 2018

The course was very well designed. The pace of the lectures are perfect unlike other course when the instructor moves very fast.