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学生对 University of Michigan 提供的 Applied Machine Learning in Python 的评价和反馈

4.6
8,605 个评分

课程概述

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....

热门审阅

AS

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.

FL

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!!

筛选依据:

701 - Applied Machine Learning in Python 的 725 个评论(共 1,574 个)

创建者 Edgar G

Sep 16, 2020

Good Content. Interesting and challenging assignments

创建者 Puchakayala S J

Jun 9, 2020

This is the best course of the best one's. Thank you!

创建者 Varun R

Jun 1, 2020

Thank you coursera for financial aid and such content

创建者 Dongxiao H

Jan 31, 2018

It is helpful for me to be familiar with scikit-learn

创建者 Paghadar A B

Sep 15, 2021

It give Execellent Start for Learn Machine Learning.

创建者 Cristian C J M

Nov 18, 2020

Muy buen curso, bastante duro, pero muy gratificante

创建者 Tue V

Mar 25, 2020

I have learnt a lot from this course. Thanks so much

创建者 Joshua A

Dec 3, 2019

An excellent overview of Machine Learning in Python.

创建者 Jose A P L

Mar 16, 2019

Muy buen curso para iniciarse en el machine learning

创建者 Dibyendu C

Oct 17, 2018

Well structured and quality lectures and assignments

创建者 Anthony K

Jul 5, 2017

So far the course is relevant and very approachable.

创建者 Aniket K S

Aug 25, 2020

Give a lot idea about implementing machine Learning

创建者 Haozhe ( X

May 30, 2020

Great course. Love the design for each assignments.

创建者 Archunan G

Dec 2, 2019

Course is interesting and nice . quiz made well .

创建者 MAINAK C

Aug 20, 2019

very nice and apt course for all types of learners.

创建者 Lutz H

Jun 17, 2019

Really well explained. Great excersices! Well done!

创建者 Aman K

Mar 5, 2019

Course Material is quite interesting and practical.

创建者 Mai N

Sep 8, 2018

Good starting points for any machine learning folks

创建者 Ebenezer A W

Nov 14, 2017

A really nice course to begin machine learning with

创建者 LEE D D

Nov 9, 2017

Perfect and hard course than Andrew Ng's ML course!

创建者 A A

Aug 4, 2017

Best introduction to sklearn library I came across!

创建者 zhang y

Oct 3, 2021

comprehensive machine learning course for beginner

创建者 Pratama A A

Jul 13, 2020

If you're beginner i suggest dont take this course

创建者 Ameya B

Jul 3, 2020

Overall good intro to actually using scikit-learn.

创建者 likejian

May 14, 2020

It’s very nice course to learn ML for the new guys