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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

8,013 个评分
1,460 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....



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!!


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.


776 - Applied Machine Learning in Python 的 800 个评论(共 1,451 个)

创建者 Syam P N

Dec 17, 2018

Excellent course. Was very helpful

创建者 Sudhir T

Aug 1, 2018

nice course and easy to understand

创建者 Armand L

Apr 24, 2018

Very Good Course ! learned a lot !

创建者 Oleg D

Mar 24, 2018


创建者 Prajay Y

Jan 11, 2022

Excellent well structured course

创建者 Natalia D P

Nov 5, 2021


创建者 BIBI I 2

Oct 31, 2021

Great course. Keep it up coursera


Oct 11, 2020

Very excellent information gained

创建者 Deekshith N

Jul 22, 2020

Very good and interesting course.

创建者 Chanaka S

Jul 21, 2020

The hardest assigment i ever done

创建者 Ovi S

May 4, 2020

Awesome for intermediate learners

创建者 Himanshu R

Apr 27, 2020

It was great learning experience.

创建者 Xiaoming Z

Jan 11, 2019

Very informative, useful practice

创建者 Hemalatha N

Oct 24, 2017

Very informative & highly useful.

创建者 Fernanda R L

Oct 9, 2017

Very good, beyond my expectations

创建者 Eunjae J

Jul 1, 2017

It was really hard, but worth it!

创建者 Deni M

May 30, 2021

G​reat course highly recommended

创建者 Dinith M

Nov 19, 2020

Learned a lot, excellent content

创建者 Gaurav R

Oct 21, 2020

best course for machine learning

创建者 Saurabh D

May 24, 2020

Very hands on. I learnt so much.

创建者 Priscila L

Nov 10, 2018

nice teacher, interesting course

创建者 Sayan G

Jun 15, 2018

Exhaustive and in depth coverage

创建者 Guido L

Feb 8, 2018

Very good, comprehensive course!

创建者 Paul M S

Jul 31, 2017

Very informative and educational

创建者 José E L

Jun 6, 2017

Excellent material and tutoring!