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学生对 University of Michigan 提供的 Applied Machine Learning in Python 的评价和反馈

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8,770 个评分

课程概述

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....

热门审阅

AS

Nov 26, 2020

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.

DB

Oct 22, 2020

EXTREMELY USEFUL AND GOOD COURSE, CONGRATULATIONS TO ALL THE PEOPLE INVOLVE.Honestly, I never thought I could learn so much in an online course, excited for the rest of the specialization

筛选依据：

726 - Applied Machine Learning in Python 的 750 个评论（共 1,599 个）

创建者 Ameya B

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Jul 3, 2020

Overall good intro to actually using scikit-learn.

创建者 likejian

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May 14, 2020

It’s very nice course to learn ML for the new guys

创建者 Abdelrahman M s A

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Feb 26, 2018

One of the best practical ML courses in the field!

创建者 ARUN S

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Nov 9, 2017

Great professor with lot of real world experience.

创建者 ChanLung

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Jul 31, 2017

Excellent Machine Learning Course for application!

创建者 Rui J (

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Nov 16, 2021

it is so much fun to write programms on your own!

创建者 Oxana M

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Dec 7, 2020

I like this cource. It gives a very good overview

创建者 Bauyrzhan A

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Nov 15, 2020

It is decent course with fair level of complexity

创建者 Anuj P

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Jun 20, 2020

tremendous knowledge for applied machine learning

创建者 SUBBA R D

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Jun 11, 2020

Very useful course especially for the beginners .

创建者 Raúl V - S

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Apr 17, 2020

Very well organized and challenging real datasets

创建者 Prachi A

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Mar 1, 2020

Amazing course for a beginner in Machine Learning

创建者 Juan S

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Feb 2, 2020

Good overview to a lot of different ML techniques

创建者 D. S

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Oct 9, 2019

Very well designed course. Learned a lot. Thanks!

创建者 Kee K Y

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Aug 8, 2021

Practical and excellent course for ML Specialist

创建者 Arturo R

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Jul 15, 2021

Very well balanced between dificuty and learning

创建者 Manan S

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May 25, 2020

Awesome Teaching and Assignemts are very usefull

创建者 Debayan M

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Jun 4, 2019

A must -learn for every aspiring data scientist.

创建者 Mischa L

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Jan 6, 2018

Great course with excellent homework assignments

创建者 Shivani R

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Jul 18, 2020

Very good course. Detailed videos & explanation

创建者 SRIHARI

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Jul 17, 2017

This is good course gives in depth information.

创建者 Muhammad F A

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Jan 1, 2021

thanks for knowledge and live to inspire,peace

创建者 Ana K A d M

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Feb 7, 2020

Excellent balance between theory and practice!

创建者 Krishna P S

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Mar 1, 2018

Excellent course. Nicely designed & delivered.

创建者 Eray Ö

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Sep 26, 2017

great course with a lot of hands-on experience