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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

8,018 个评分
1,463 条评论


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....



Sep 8, 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


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!!


1226 - Applied Machine Learning in Python 的 1250 个评论(共 1,454 个)

创建者 Maxim P

Sep 15, 2018

Nice there could just be a bit more of a case study to see the difference and decision ways in practices

创建者 Jesús P

Jan 5, 2018

great course but could be improved with a better explaining of the class on board for abstract concepts.

创建者 shashank m

Jul 16, 2019

Very intuitive course...and carefully designed so that it does not overwhelm the students with details

创建者 ZHAI L

May 11, 2018

Compared to previous two courses in this specialization, this course need more time for self-learning.

创建者 Justin M

Apr 11, 2018

Great course overall. Only reason for 4 stars is some of the assignments could use a bit more clarity.

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 Vishwa M

Sep 3, 2021

Course Content was excellent. I really learned a lot. Assignment 4 was a hassle to submit though.

创建者 Stephen R

May 8, 2018

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

创建者 J N

May 23, 2021

Teaching by the professor is very good and i learnt every thing from scratch thankyou coursera

创建者 Pierre D

May 1, 2021

Interesting course. Last exercise allows understanding how to use ML, when you are all alone.

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 5, 2020

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

创建者 Koffi K

Oct 14, 2019

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

创建者 Nicholas P

Dec 29, 2020

Good content and teacher but needs more interactivity before the final project every week

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 3, 2020

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

创建者 Falak S

Oct 28, 2020

It's really a great course for the beginner to begin with the machine learning basics.

创建者 Haldankar S N

May 29, 2020

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


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 Sabin A

May 31, 2021

Nice course helps understanding the basic ideas about machine learning algorithms.

创建者 Setiadi M

Jul 27, 2020

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