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Applied Machine Learning in Python に戻る

ミシガン大学(University of Michigan) による Applied Machine Learning in Python の受講者のレビューおよびフィードバック

4.6
4,368件の評価
758件のレビュー

コースについて

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....

人気のレビュー

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

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!!

フィルター:

Applied Machine Learning in Python: 151 - 175 / 740 レビュー

by 陈熠

Aug 13, 2017

Very good machine learning course working on python with little mathematics.

by Dongliang Z

Dec 22, 2017

Very good lecture for beginner:easy to understand.

Also good assignment: force you to use what you learned in the course.

The discussion forum is helpful when you meet difficulties in assignments and quiz.

by Peter D

Nov 06, 2017

Nice pragmatic approach how to apply machine learning. Compelling examples, datasets and useful tips how to visualise features.

by Fabio C

Jun 22, 2017

The course is well done and both the lectures and the practical assignments have generally a high quality. If you come from a theoretical background, be aware that this is a very "high level" course, meaning that a lot of attention is put on the practical application of the different ML methods (using the sci-kit learn library in python), but very little is said about their mathematical foundations.

by Dylan E

May 03, 2018

I enjoyed this course it was fun and very informative. This course also gave me a bunch of resources such as The Elements of Statistical Learning which is a great book!

by Arun S

Nov 09, 2017

Great professor with lot of real world experience.

by Sridhar I

Dec 21, 2017

A great crash course in some of the basics of machine learning on Python. Although not explicitly covered, the assignments helped me gain an understanding on the Jupyter framework & pandas.

The final assignment was definitely a cherry on top that let me gain a very vivid insight into the field.

by Marcin C

Apr 29, 2018

Heavy, but extremely valuable course

by Ali A

Mar 22, 2018

Excellent!!!

by Jiangming Y

Mar 04, 2018

This is an excellent course, from which I have learnt a lot about machine learning with Python.

by Matias B M

Aug 15, 2017

Challenging and rewarding. Wouldn't have it any other way.

by Christos G

Sep 01, 2017

Following the first 2 sessions of this specialisation, this one seems easy and gives the student a lot of confidence. Make sure you follow the sequence suggested in this specialization, even if you do not plan to continue with Text Mining and Social Networks.

by Vladimír L

Jan 18, 2018

great course with a high value added

by Biju S

Oct 12, 2017

Very tough to finish. Big gap with material and assignments

by Nathan R

Oct 17, 2017

Excellent course. A practical application of the concepts in Python/sklean.

by Evgeny V

Apr 04, 2018

Excellent course!

by Vladimir

Sep 27, 2017

A course that gives not only solid understanding of Machine Learning, but provides with skills to actually practice it on real world datasets. Highly recommended.

by Joan P

Nov 05, 2017

Very interesting last programming assignment

by Steven L

Apr 08, 2018

Very practical introduction to using Python for machine learning - less focused on theory and more focused on how to use the sklearn library and proper use cases for different classifiers and regressors.

by Krishna D

Dec 09, 2017

Excellent Course. Well presented and good organized python notebooks, quiz and assignments.

Enjoyed the project very much.

Looking forward for future classes

by Michael D

Jul 19, 2017

I thought this was a fascinating course that tried to do the near impossible and succinctly summarise the key techniques of machine learning. And it did that very well. Very challenging tasks, but also overall inspiring for the next step.

by Srinivas B

Mar 25, 2018

Its almost great, just short of 5 star rating! Liked the hands-on examples more

by Guido L

Feb 08, 2018

Very good, comprehensive course!

by Tongsu P

Feb 08, 2018

Really challenging course!

by Madalina-Mihaela B

Jul 18, 2017

Awesome course. Very practical!