Chevron Left
返回到 Applied Machine Learning in Python

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

4.6
7,981 個評分
1,452 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!!

OA

2017年9月8日

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

篩選依據:

701 - Applied Machine Learning in Python 的 725 個評論(共 1,442 個)

創建者 Dario M

2019年7月12日

So far the best course in this specialization

創建者 Rohit M S

2019年3月22日

The Course is amazing. you get to learn a lot

創建者 Xiaoyue Z

2018年7月30日

A very helpful and confidence-building class!

創建者 Ruyang L

2018年4月20日

Very interesting course, enjoyed it very much

創建者 zios s

2017年11月23日

great course very useful in data science job.

創建者 Om P

2020年5月17日

perfect for beginners! thank you, professor!

創建者 Pilar V

2019年9月14日

Super interesting course and specialization!

創建者 Joan P

2017年11月5日

Very interesting last programming assignment

創建者 David M

2017年7月7日

Great introduction to Scikit-learn tool set.

創建者 Danish R

2017年7月2日

P.S.: This is not an easy course to complete

創建者 Amey k

2022年1月9日

best course for machine learning enthusiast

創建者 sudipta d

2021年10月29日

this course helps me to building my skills.

創建者 roberto T

2020年8月17日

Good course, especially on the applied side

創建者 Ranjit K

2020年7月26日

Great Learning with good examples and tasks

創建者 Olivier R

2020年7月1日

Highly Recommended, the Instructor is great

創建者 刘宇轩

2017年12月14日

The last homework is great and interesting.

創建者 Thodoris N P

2017年10月26日

Most complete Machine learning course ever.

創建者 MIFTAHUL J

2020年11月30日

very organized and helpful course. Thanks!

創建者 Anurag B

2019年6月8日

Great Content, Great Delivery, Thumbs Up!!

創建者 Darío A

2018年6月2日

Excellent course to get into sci kit leran

創建者 Drew O

2017年10月8日

Great course. Challenging and informative.

創建者 Mohsen

2017年8月3日

I've learned a lot. Very practical course!

創建者 Ayush R

2020年11月9日

very well details of concept and learning

創建者 Puran Z

2020年6月1日

Great course. I love it, thank professor.

創建者 MOH S

2020年5月19日

Excellent content and perfect instructor.