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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
6,752 个评分
1,215 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

OA

Sep 09, 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

FL

Oct 14, 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:

1026 - Applied Machine Learning in Python 的 1050 个评论(共 1,196 个)

创建者 Manjeet K

Sep 14, 2019

Easy to learn the course, just be focussed. Its an applied ML course, not to expect any mathematics.

创建者 Ulka K

Feb 27, 2020

I found the dataset in the last assignment difficult to interprit. I was hoping for a simpler one.

创建者 Stephen R

May 08, 2018

Wish there were a little more theory, realize it's an "Applied" course but still seemed lacking

创建者 Michel H

Jan 23, 2020

helpfull, but so many information in little time. Difficult to get clarified the ideas behind

创建者 Samantha

Apr 05, 2020

Very great courses ! It helps to deepen my knowledge in Machine learning. Very recommend it!

创建者 Koffi M K

Oct 14, 2019

A part from some small issues when doing the last assignment(4), Everything was all right.

创建者 WhiteCR

Feb 15, 2020

Good course for practicing machine learning algorithms with Python Sci-kit Learn package.

创建者 Massimo T

Nov 12, 2019

The python packages used in the course are becoming outdated

adding useless difficulties.

创建者 soymilk

Oct 03, 2020

Contents of lecture are good but the assignments got many problems that should be fixed

创建者 Haldankar S N

May 29, 2020

too much content for 4 weeks course as compared to other courses in the specialization

创建者 YJFKD

May 19, 2020

Good course if you want to know how to build machine learning models via scikit-learn.

创建者 Sumit t

Jun 23, 2020

Nice Course and good explanation about practical implementation of machine learning

创建者 Niv B

Jul 30, 2018

On 1x speed, I'd rate it 3 stars, on 1.5x its 4.

The professor just speaks too slow.

创建者 Setiadi

Jul 27, 2020

This course is good for somebody wanna to know about the Machine Learning, thanks.

创建者 tqch

Jul 24, 2020

Just hoping the problems in assignments/quizzes could be explained more clearly.

创建者 Claire-Isabelle C

Jun 24, 2017

I learned A LOT in this course and was pretty proud to pass all the assignments.

创建者 Saori Y

Jul 22, 2020

The course was really good! However, auto-grading system need to be updated....

创建者 SAYANTAN B

May 09, 2020

Very nice and informative course..Keep it up. This course has helped me a lot.

创建者 Hanchi W

May 18, 2019

Good content, some coding assignments are hard to submit(csv file not found)

创建者 Bharat R

Aug 22, 2017

Nice course. Multiple choice quizzes could have been worded a bit better.

创建者 Grace Y

May 15, 2020

the material for self-learning after classes is not comprehensive enough.

创建者 Douglas P

May 28, 2018

Generally worth while but the automatic grading system could be improved.

创建者 Daniel A

Sep 01, 2018

Very useful. It's the right course to take after Andrew Ng ML course.

创建者 Shwetank A

Jul 23, 2019

Algorithim are not explained much better, just coding is explained.

创建者 Hardik A

Jan 04, 2018

An amazing course for learning the application of machine learning.