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學生對 密歇根大学 提供的 Applied Machine Learning in Python 的評價和反饋

4.6
4,794 個評分
834 條評論

課程概述

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....

熱門審閱

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!!

篩選依據:

201 - Applied Machine Learning in Python 的 225 個評論(共 816 個)

創建者 Quan S

May 08, 2019

Course materials are very systematic and instructive, and the professor teaches very clearly. I like this course and recommend it.

創建者 Flavia A

Mar 11, 2018

Practical class to learn well-known models and scikit-learn. The practice tests are great to help you move from theory to practice.

創建者 Ivan S F

Mar 23, 2019

Very good course. Not very deep, but definitively very wide and appropriate for an overview course of machine learning in python.

創建者 abdulkader h

Jul 04, 2017

I appreciate so much this course even it was so dense and slitly short. It would be useful to extend it over several weeks again.

創建者 Mahindra S R

Mar 28, 2020

Useful for understanding the application part of ML whereas Andrew Ng's course gives a more in-depth understanding of the topics

創建者 SURENDRA O

Dec 25, 2018

The course was very well designed. The pace of the lectures are perfect unlike other course when the instructor moves very fast.

創建者 Ram N T

Jan 02, 2020

The course material and Professor Kevyn Collins-Thompson is awesome. A person who's seeking to learn ML should try this course.

創建者 STEVEN V D

Jan 21, 2018

World class course.

Covers a lot of core machine learning subjects in an accessible way with a practical focus in Python.

Thanks!

創建者 Peter D

Nov 06, 2017

Nice pragmatic approach how to apply machine learning. Compelling examples, datasets and useful tips how to visualise features.

創建者 Manoj K K M

Jun 30, 2018

For applied machine learning, outstanding. It could be improved with bit more theory, which gives more insight to the concept.

創建者 SHRISH T

Aug 20, 2017

Very good course, for people who want to apply Machine Learning without worrying too much about the theoretical aspects of it.

創建者 Lam M

Jun 09, 2017

Very well designed courses! There are many materials to go in depth even if you have done Python Machine Learning in the past.

創建者 Roger A G

Jun 03, 2019

Excellent course! It teaches you the basics of Machine Leaning, and merges the knowledge already acquired in the first module

創建者 Stephen

May 03, 2019

Had all the basics of Machine Learning algorithms, but they need to update the syllabus with some trending boosting concepts

創建者 Ivan Y

Oct 24, 2018

Great! loved the final project, which is a machine learning project that you can actually put on your resume and talk about!

創建者 Muhammad S

Apr 01, 2020

I am very satisfied with this course. I learnt a lot of techniques from the course that I can apply in my research project.

創建者 Hrishikesh B

Mar 14, 2019

very good course for intermediate level learners .learned a lot in such a short time.thanks to prof.Kevyn Collins-Thompson.

創建者 Bui T D

Oct 30, 2018

It is a great course with best practices. Thank you for your time and consideration. I learnt many things from your course.

創建者 Martin U

Jan 11, 2019

Tough class, learned not to give up and keep trying. Even went back and redid some quizzes in order to get a better grade.

創建者 Boyan Z

Dec 16, 2019

A very useful course that gives very good overview for the applied side of machine learning for solving various problems.

創建者 TEJASWI S

Aug 01, 2019

Concepts were clearly taught and helped me gain knowledge in techniques used in machine learning. Recommend it to others.

創建者 Henri

Mar 23, 2019

Excellent course, but be ready to spend some time on debugging the automatic grader especially for the final assignment!

創建者 Sandeep S

Aug 03, 2017

Covered a lot of topics. Helps a beginner to get a good overview of the various tools and concepts on Machine Learning.

創建者 João R W S

Jul 04, 2017

Excellent course! Learned a lot both about the concepts and how to apply the methods using scikit-learn. Very good job!

創建者 Dave C

Oct 25, 2019

Very enjoyable, informative and I really believe I can go on and build my own ML system with confidence. Recommended.