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學生對 密歇根大学 提供的 Applied Machine Learning in Python 的評價和反饋

4,368 個評分
758 個審閱


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....



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


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!!


226 - Applied Machine Learning in Python 的 250 個評論(共 739 個)

創建者 Aniket B

Jun 24, 2017

Awesome course

創建者 Jose S

Jun 16, 2017

Great course. The material is well thought, the assignments are excellent. I learned a lot and I am already leveraging what I learned in the course at work.

創建者 Saiapin A

Jul 24, 2017

This is a great course for those who want to get acquainted with machine learning basics as well as its applications.

創建者 Nitin P

Feb 28, 2018

Very Interesting and fascinating Course of Machine Learning

創建者 xixicy

Apr 10, 2018

The content (slides, python scripts) is very structured. The lecturer explained very clearly. The reference articles were super inspiring. Also, the assignment is very well designed and relevant to what's covered (in comparison, some other courses might have very difficult assignments which need much more self-learning and cause frustration). Thank you!!

創建者 Sayan G

Jun 15, 2018

Exhaustive and in depth coverage

創建者 Oleh Z

Feb 27, 2018


創建者 Mykhailo L

Jan 06, 2018

Great course with excellent homework assignments

創建者 Guneet B

Apr 02, 2018

High Quality resources and materials

創建者 Rob N

Oct 15, 2017

This course was challenging and extremely interesting. The long and detailed lectures and excellent lecture notes covered the material very thoroughly for an online course.

創建者 Hari S R V

May 30, 2018

Great course

創建者 Darío A

Jun 03, 2018

Excellent course to get into sci kit leran

創建者 Saifullah

Jun 08, 2018

Well designed for practicing, helps a lot in applying ML in python

創建者 Ranabir G

Jun 04, 2018

Assignments are good

創建者 Mostafa A A

Sep 23, 2017

This is the most useful machine learning course in the internet. It helped me to understand machine learning algorithms very well that I never saw in other courses. This course covers most of the machine learning algorithms that needed nowadays. Thanks to Michigan University and Coursera to make this course to be available online.

創建者 Чижов В Б

Nov 15, 2017

Very interesting and informative! The material outlined in the course, difficult to understand, IMHO, but the organizers and the teacher managed to present it in an accessible form. Special thanks to Kevyn Collins-Thompson for his lectures and Sophie Grenier for her work and attention to the forum.

創建者 Muhammad A

Jun 08, 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.

創建者 Anirudh S

Mar 14, 2018

Fantastically explained. with jupyter notebooks! appreciate your effort.

創建者 Mohamad F I

Jun 25, 2018

A good course focusing on basics of machine learning. Great for beginner with python knowledge.

創建者 Benjamin M L

Mar 14, 2018

Excellent course, easy to understand, useful and enjoyable to do! Two minor comments: it took me a longer than the estimated times to complete the Quizzes; I have Python programming proficiency and a small amount of background in Machine Learning. I would have preferred the final assessment to have an extension to it which required a more advanced model.

創建者 József V

Apr 29, 2018

Broad range of ML knowledges is covered!

創建者 Sunil S

Jul 05, 2018

Great course for implementing machine learning using python.

創建者 Ivan Y

Oct 24, 2018

Great! loved the final project, which is a machine learning project that you can actually put on your resume and talk about!

創建者 Juan M C T

Oct 23, 2018

Great course

創建者 Ray B

Oct 29, 2018

Good intro to scikit-learn