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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
7,138 个评分
1,295 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:

1251 - Applied Machine Learning in Python 的 1274 个评论(共 1,274 个)

创建者 Sai P

Jun 3, 2020

There were a few corrections made during the videos which ended being quite confusing.

创建者 Philip L

Oct 30, 2017

The assignments are extremely difficult, professor is a bit dry during lectures.

创建者 Pakin S

Jan 10, 2020

How can i pass without reading discuss about problem with notebook

创建者 Hao W

Aug 27, 2017

The homework is too easy to improve our understanding of ML

创建者 M S V V

Jun 29, 2020

Too much of information compressed within a short span.

创建者 José D A M

Jun 21, 2020

Too fast, yet too difficult. Needs deeper explanation.

创建者 Navoneel C

Nov 21, 2017

Nice and Informative but not practically effective

创建者 Priyanka v

May 8, 2020

if it is more detailedthen it will be more useful

创建者 Sameed K

Mar 15, 2018

have to figure out a lot of things on you own.

创建者 Andy S

Jun 4, 2019

It could have been better with more examples.

创建者 Shan J

Apr 12, 2020

The explanation could have been much better.

创建者 Jeremy D

Jul 10, 2017

The topics were good, but too many were d

创建者 Ryan S

Dec 12, 2017

Homeworks are inconvenient to submit

创建者 PIYUSH A

May 16, 2020

The narration was a bit boring.

创建者 shreyas

Jun 29, 2020

Teacher wasn't very good

创建者 Abir H R

Jun 30, 2020

very long videos

创建者 Wojciech G

Oct 28, 2017

To fast paced.

创建者 Aarya P

Sep 30, 2020

Really disappointed with the course ...you may ask why??

The first thing is the instructor , super boring. The instructor (with all due respect) was very dry and the lectures were super uninteresting. When he keeps on talking code, but doesn't really explain stuff. The material and lectures were dry and colorless.

Me without having good statistics background had huge difficulties understanding the concepts. Please i recommend everyone to have good knowledge in statistics before starting the course. ABSOLUTELY NOT THE BEGINNER LEVEL AND NEITHER INTERMIDIATE LEVEL .the course is quiteeeee difficult.

You also need to have a lot of self study , which i am not a big fan of. I hope they make the course more fun rather than a man constantly talking on the screen .

创建者 Oswaldo C

Aug 22, 2020

Los videos no son suficientemente extensos ni para explicar el código, ni para explicar la teoría detrás de los algoritmos, se queda a medio camino de los dos siendo insuficiente en ambos casos

创建者 David C

Nov 8, 2020

Not as good as prev. courses. Univ. of mic. should update or get ride of this module

创建者 Aditya M

Jul 17, 2020

Can't the lecturer use proper slides with proper diagrams for a better explanation.

创建者 SHREYAS D

Aug 14, 2020

Things in the beginning are not explained properly

创建者 Konark Y

May 10, 2020

many issues while submitting assignments

创建者 Oleg G

May 16, 2020

enrolled by mistake want to u nenroll