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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

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8,058 個評分

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

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

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!!

篩選依據：

1301 - Applied Machine Learning in Python 的 1325 個評論（共 1,465 個）

創建者 Anendra G

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2018年4月30日

Awesome theory about machine learning concepts.

創建者 Catherine M

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2021年3月1日

Nice course. A lot of ML models get presented.

創建者 harsh a

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2018年2月3日

Good course.

Thanks to entire team

Harsh Arora.

創建者 Tianyu Z

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2019年6月19日

Some concepts should be introduced in detail.

創建者 Amita D

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2018年5月18日

Need more information about more algorithms

創建者 CHAPPIDI S N B

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2022年1月16日

Excellent way of teaching and learned well

創建者 Souvik M

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2022年1月23日

where is my certificate?????????????????

創建者 Ruben W

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2019年9月8日

Best course so far in this specialisation

創建者 Alan F

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2018年2月28日

Good course but there's a lot of material

創建者 Abdulwaheed M

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2020年6月17日

Teaching is very good and it is helpfull

創建者 Alperen B O

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2020年12月16日

I get late feedback for lab assignments

創建者 Ramya K

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2019年7月15日

Well-organized but assignments too easy

創建者 Supratim D

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2017年8月10日

Very informative but bit too difficult.

創建者 ROHIT J

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2020年8月2日

very helpfull.thanks for creating this

創建者 Xiang C

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2020年5月12日

It's good to learn how to use sklearn.

創建者 Jagadish C A

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2019年9月19日

Gives good overview of ML using Pyton

創建者 Shreekant G

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2019年7月17日

Really taught best ML algorithms

創建者 xingkong

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2017年8月9日

quiz is harder than assignment.

創建者 shreyash t

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2020年7月28日

overalll good way to start ml

創建者 Vaibhav S

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2020年5月27日

way better than last teacher.

創建者 Nicolas B

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2017年7月5日

Muy buen curso, muy completo.

創建者 SANSKRITI G 2

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2021年10月26日

it was an amazing experience

創建者 李祥泰

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2017年8月15日

Nice courses with nice quiz!

創建者 刘倬瑞

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2017年7月29日

Useful, though a little easy

創建者 Landon M L

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2017年7月9日

the discussion forum is good

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