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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

7,858 个评分
1,429 条评论


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.


801 - Applied Machine Learning in Python 的 825 个评论(共 1,414 个)

创建者 Riahi L

Oct 19, 2017

very good course, I enjoyed it

创建者 Ruchi S

Aug 9, 2017

deep yet simple to understand.

创建者 Sajit K

Jun 25, 2017

Insightful and hands on course


Sep 8, 2021

it was a very good experience

创建者 Chris P

Mar 9, 2021

Great survey of ML w/ Sklearn

创建者 Devjyoti M

Aug 1, 2020

It was an amazing experience.

创建者 Renjith

Apr 8, 2020

Awesome course, good learning

创建者 Dongsoo J K

Jul 18, 2017

Very good and straightforward

创建者 Araceli Z

Aug 8, 2021

Great course and challenging


Jun 23, 2020

great experience in learning

创建者 Rana S A

Jun 8, 2020

Very much Informative Course


May 17, 2020

very nice course.very useful

创建者 Anurag M

Jun 9, 2019

Excellent material for study

创建者 John H E

Mar 16, 2019

I truly enjoyed this course.

创建者 John D L C

Dec 27, 2018

This is an excellent course.

创建者 Amrith M

Jul 8, 2017

Yet another Awesome course!!


Jun 17, 2020

Great Exposure of knowlwdge

创建者 Fernandes M R

Jun 16, 2020

The best course a ever had.

创建者 narra s s

May 10, 2020

Great platform for Learning

创建者 P.Raja S

Apr 25, 2020

nice and informative course

创建者 Xinzhi Z

Jun 23, 2019

Great course! Very helpful.

创建者 Tianyang Z

Jul 6, 2017

great course. Learned a lot

创建者 Kshitij K

Sep 17, 2020

Very helpful for my career

创建者 Vinit K

May 7, 2020

Great learning experience.

创建者 Ray B

Oct 28, 2018

Good intro to scikit-learn