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学生对 密歇根大学 提供的 Applied Machine Learning in Python 的评价和反馈

8,251 个评分


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....



Oct 13, 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!!


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.


1276 - Applied Machine Learning in Python 的 1300 个评论(共 1,500 个)

创建者 Falak S

Oct 28, 2020

It's really a great course for the beginner to begin with the machine learning basics.

创建者 Haldankar S N

May 29, 2020

too much content for 4 weeks course as compared to other courses in the specialization


May 19, 2020

Good course if you want to know how to build machine learning models via scikit-learn.

创建者 Sumit t

Jun 23, 2020

Nice Course and good explanation about practical implementation of machine learning

创建者 Niv B

Jul 30, 2018

On 1x speed, I'd rate it 3 stars, on 1.5x its 4.

The professor just speaks too slow.

创建者 Sabin A

May 31, 2021

Nice course helps understanding the basic ideas about machine learning algorithms.

创建者 Setiadi S

Jul 27, 2020

This course is good for somebody wanna to know about the Machine Learning, thanks.

创建者 tqch

Jul 24, 2020

Just hoping the problems in assignments/quizzes could be explained more clearly.

创建者 Claire-Isabelle C

Jun 24, 2017

I learned A LOT in this course and was pretty proud to pass all the assignments.


Jan 1, 2023

I learn many things to this course Thank You for make this deep concept course.

创建者 Saori Y

Jul 22, 2020

The course was really good! However, auto-grading system need to be updated....


May 9, 2020

Very nice and informative course..Keep it up. This course has helped me a lot.

创建者 Lucas C R

Jul 29, 2022

Classes and exercise are really good, but the assignement is really terrible


Oct 31, 2020

Please add the explanation on concepts on board.. sure that will impact more!

创建者 Hanchi W

May 18, 2019

Good content, some coding assignments are hard to submit(csv file not found)

创建者 Vishwanath V

Dec 19, 2020

Its well designed course providing good overall concept involved in the ML.

创建者 Bharat R

Aug 22, 2017

Nice course. Multiple choice quizzes could have been worded a bit better.

创建者 Grace Y

May 15, 2020

the material for self-learning after classes is not comprehensive enough.

创建者 Douglas P

May 28, 2018

Generally worth while but the automatic grading system could be improved.

创建者 Tin H P

Jan 15, 2023

Quite basic ML knowledge. More challenging assignments should be added.

创建者 Daniel A

Sep 1, 2018

Very useful. It's the right course to take after Andrew Ng ML course.

创建者 Shwetank A

Jul 23, 2019

Algorithim are not explained much better, just coding is explained.

创建者 Hardik A

Jan 4, 2018

An amazing course for learning the application of machine learning.

创建者 Tom M

Sep 27, 2017

Clean programming examples. A little simplistic for advanced users.

创建者 Davide M

Oct 24, 2018

Should be an harder final assignement, but a great course overral!