Chevron Left
返回到 Applied Machine Learning in Python

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

4.6
7,974 个评分
1,452 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

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:

726 - Applied Machine Learning in Python 的 750 个评论(共 1,442 个)

创建者 Jay G

Mar 20, 2020

Thank you so much for this amazing course

创建者 Yang L

Nov 28, 2019

love the final assignment. Had great fun!

创建者 Gustavo H d N

Aug 31, 2019

Good balance between theory and practice.

创建者 dan s

Dec 30, 2017

Fantastic Course. I highly recommend it.

创建者 Tinniam V G

Sep 7, 2017

Terrific course. Many thanks to the Prof!

创建者 Nguyen T S

Nov 16, 2021

T​hank you! this course is very helpful.

创建者 Vaneeza I

Aug 29, 2021

Highly recommended courses for beginners

创建者 William H

Sep 2, 2019

Excellent instructor and course material

创建者 Patrick K

Nov 22, 2018

Very nicely explained. Highly recommend.

创建者 József V

Apr 29, 2018

Broad range of ML knowledges is covered!

创建者 hema m M

Jun 30, 2020

Very helpful and interesting resources.

创建者 Vishant J

Apr 18, 2020

excellent course for beginners as well!

创建者 Alexander G

Jul 15, 2019

Nice course on machine learning basics!

创建者 Nan L

Jun 17, 2018

I think this course is difficult for me

创建者 Ranjeetha V

May 16, 2022

E​xcellent teacher and well explained!

创建者 Henrique G A

Jan 25, 2021

Best course with the best professor!!!

创建者 Pavan M

Jan 19, 2021

Course is Good and Very well presented

创建者 Muhammad E

Oct 26, 2020

very good course totally recommend it

创建者 RAMISETTI B R

Feb 7, 2020

wow!!!great feeling from learning here

创建者 Mariano S C

Oct 25, 2019

great course, excellent teaching staff

创建者 Shadi A

May 6, 2019

Best Instructor and simple explanation

创建者 Nilesh I

Oct 5, 2018

Practical, I liked the evaluation part

创建者 SANKURU M K

May 17, 2020

very nice course.usefull for beginers

创建者 Marion T

May 31, 2019

good introduction to machine learning

创建者 Michael T

Feb 21, 2019

Great content and reference materials