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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
7,749 個評分
1,415 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

FL
2017年10月13日

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!!

AS
2020年11月26日

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.

篩選依據:

351 - Applied Machine Learning in Python 的 375 個評論(共 1,400 個)

創建者 Quan S

2019年5月8日

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

2018年3月11日

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 Aniket S K

2020年7月1日

Good Course. Not for beginners starting with Machine Learning. Intermediate level. Prior knowledge of python libraries would help.

創建者 Émile J

2020年5月19日

The exercices and evaluations are more complex than in the previous courses in this short program, but also much more instructive.

創建者 Himanshu B

2020年5月15日

It was really an excellent well designed course, I gained valuable information that I will use as a business analytics in future.

創建者 Ivan S F

2019年3月23日

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

2017年7月4日

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 usama i

2020年10月12日

Excellent course to understand and learn about how to work with available classifiers in scikit learn. Thanks for this course :)

創建者 Ari W R

2020年8月28日

it is a pleasure to learn about machine learning course. I can remind and study again about the main things in machine learning.

創建者 Jason L

2020年8月26日

Very solid course. Covers so many key machine learning concepts in a short period of time. Week 2 is intense - but awesome!

創建者 Mahindra S R

2020年3月27日

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

2018年12月25日

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 Yiwu T

2021年4月16日

Broad coverage.

Good project assignment.

Staff not answering questions very promptly at discussion forum.

Cannot download slides.

創建者 Ram N T

2020年1月2日

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

2018年1月21日

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

2017年11月6日

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

2018年6月30日

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

2017年8月20日

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

創建者 Raga

2017年6月9日

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

2019年6月3日

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

創建者 Stephen S

2019年5月3日

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

2018年10月24日

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

2020年4月1日

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

2019年3月14日

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