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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
7,745 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.

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626 - Applied Machine Learning in Python 的 650 個評論(共 1,400 個)

創建者 SAFVAN M S P

2020年8月17日

Amazing course, full of insights. Very well structured.

創建者 Thales A K N

2020年7月3日

Best Course in the Specialization!!! I learned so much!

創建者 Maryanne K

2020年5月4日

Great! Fun and useful course. Concepts explained well.

創建者 Ankush G

2020年1月14日

A good stepping stone towards a career in data science.

創建者 Fei W

2019年11月6日

The course is very well structured, highly recommended!

創建者 Nikhil N

2021年7月6日

W​onderful Course but slightly difficult for beginners

創建者 Kunal K

2020年4月22日

it good to basics and devloped the skill in that field

創建者 Ajay S

2019年1月29日

great course thanks for financial aid for the course .

創建者 Kristin A

2019年1月12日

Great intro to the tools of machine learning in Python

創建者 Walter M

2018年7月29日

Good class. The asignements made me a better engineer.

創建者 Alonso S A

2017年11月10日

Very usefull, easy to understand and full of examples.

創建者 Кочеткова А М

2020年12月8日

Interesting lectures, everything is clear, thank you!

創建者 Edgar G

2020年9月17日

Good Content. Interesting and challenging assignments

創建者 Puchakayala S J

2020年6月9日

This is the best course of the best one's. Thank you!

創建者 Varun R

2020年6月1日

Thank you coursera for financial aid and such content

創建者 Dongxiao H

2018年1月31日

It is helpful for me to be familiar with scikit-learn

創建者 Paghadar A B

2021年9月15日

It give Execellent Start for Learn Machine Learning.

創建者 Cristian C J M

2020年11月18日

Muy buen curso, bastante duro, pero muy gratificante

創建者 Tue V

2020年3月25日

I have learnt a lot from this course. Thanks so much

創建者 Joshua A

2019年12月3日

An excellent overview of Machine Learning in Python.

創建者 Jose Á P L

2019年3月16日

Muy buen curso para iniciarse en el machine learning

創建者 Dibyendu C

2018年10月17日

Well structured and quality lectures and assignments

創建者 Anthony K

2017年7月5日

So far the course is relevant and very approachable.

創建者 Aniket K S

2020年8月25日

Give a lot idea about implementing machine Learning

創建者 Haozhe ( X

2020年5月31日

Great course. Love the design for each assignments.