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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

8,017 个评分
1,463 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....



Sep 8, 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


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.


1301 - Applied Machine Learning in Python 的 1325 个评论(共 1,454 个)

创建者 Alan F

Feb 28, 2018

Good course but there's a lot of material

创建者 Abdulwaheed M

Jun 17, 2020

Teaching is very good and it is helpfull

创建者 Alperen B O

Dec 16, 2020

I get late feedback for lab assignments

创建者 Ramya K

Jul 15, 2019

Well-organized but assignments too easy

创建者 Supratim D

Aug 10, 2017

Very informative but bit too difficult.


Aug 2, 2020

very helpfull.thanks for creating this

创建者 Xiang C

May 12, 2020

It's good to learn how to use sklearn.

创建者 Jagadish C A

Sep 19, 2019

Gives good overview of ML using Pyton

创建者 Shreekant G

Jul 17, 2019

Really taught best ML algorithms

创建者 xingkong

Aug 9, 2017

quiz is harder than assignment.

创建者 shreyash t

Jul 28, 2020

overalll good way to start ml

创建者 Vaibhav S

May 27, 2020

way better than last teacher.

创建者 Nicolas B

Jul 5, 2017

Muy buen curso, muy completo.


Oct 26, 2021

it was an amazing experience

创建者 李祥泰

Aug 15, 2017

Nice courses with nice quiz!

创建者 刘倬瑞

Jul 29, 2017

Useful, though a little easy

创建者 Landon M L

Jul 9, 2017

the discussion forum is good

创建者 Rizvaan M

May 21, 2020

This was a great course.

创建者 Biswakarmi K

Aug 18, 2021

v​ery helpful course..

创建者 Yassin B M

Jul 17, 2020

Good Course , Thanks!!

创建者 Burak

Sep 30, 2018

good for scikitlearn.

创建者 David P

Aug 4, 2021

A really good course

创建者 Bama

Jul 11, 2020

This course is good.

创建者 Abhav T

Jun 3, 2020

Nice course to study

创建者 Bhoris D

Jan 17, 2021

Quite challenging.