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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

4.6
8,013 个评分
1,460 条评论

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

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!!

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.

筛选依据:

801 - Applied Machine Learning in Python 的 825 个评论(共 1,451 个)

创建者 Jun S

Dec 30, 2020

Excellence course for beginners

创建者 Adish P

May 28, 2020

Excellent Course. Very helpful.

创建者 Vikas K

Dec 9, 2019

best course in detailed version

创建者 ASHISH G

Jul 17, 2019

excellent course for beginners!

创建者 Fadhel A

May 28, 2019

whole new informations for me.

创建者 Li T

Oct 28, 2017

Informative course. Five stars!

创建者 Ivan P

Aug 14, 2017

Very good course for beginners)

创建者 Madalina-Mihaela B

Jul 18, 2017

Awesome course. Very practical!

创建者 Jim S

Jul 1, 2017

Excellent content and delivery.

创建者 Keziah S T K S

Dec 6, 2021

Good explanations, good module

创建者 dean w

Nov 15, 2020

Very Challenging and Rewarding

创建者 Koshanov A

Oct 15, 2020

очень удобно, кратко и понятно

创建者 Paul S

Apr 16, 2020

Very interesting and enjoyable

创建者 Elizabeth N

Apr 2, 2020

Very good applied introduction

创建者 Muhammad Z H

Sep 1, 2019

Learnt a lot Professor. Thanks

创建者 RAJESH M

Aug 6, 2019

Nice course, Practice oriented

创建者 Jan P

Jul 11, 2018

great course - I learnt a lot!

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

创建者 DIVYA G

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