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学生对 密歇根大学 提供的 Applied Machine Learning in Python 的评价和反馈

8,053 个评分


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....



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.


Sep 8, 2017

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


651 - Applied Machine Learning in Python 的 675 个评论(共 1,465 个)


Aug 17, 2020

Amazing course, full of insights. Very well structured.

创建者 Thales A K N

Jul 3, 2020

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

创建者 Maryanne K

May 4, 2020

Great! Fun and useful course. Concepts explained well.

创建者 Ankush G

Jan 14, 2020

A good stepping stone towards a career in data science.

创建者 Fei W

Nov 6, 2019

The course is very well structured, highly recommended!

创建者 Nikhil N

Jul 6, 2021

W​onderful Course but slightly difficult for beginners

创建者 Kunal K

Apr 22, 2020

it good to basics and devloped the skill in that field

创建者 Ajay S

Jan 29, 2019

great course thanks for financial aid for the course .

创建者 Kristin A

Jan 12, 2019

Great intro to the tools of machine learning in Python

创建者 Walter M

Jul 29, 2018

Good class. The asignements made me a better engineer.

创建者 Alonso S A

Nov 10, 2017

Very usefull, easy to understand and full of examples.

创建者 Кочеткова А М

Dec 8, 2020

Interesting lectures, everything is clear, thank you!

创建者 Edgar G

Sep 17, 2020

Good Content. Interesting and challenging assignments

创建者 Puchakayala S J

Jun 9, 2020

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

创建者 Varun R

Jun 1, 2020

Thank you coursera for financial aid and such content

创建者 Dongxiao H

Jan 31, 2018

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

创建者 Paghadar A B

Sep 15, 2021

It give Execellent Start for Learn Machine Learning.

创建者 Cristian C J M

Nov 18, 2020

Muy buen curso, bastante duro, pero muy gratificante

创建者 Tue V

Mar 25, 2020

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

创建者 Joshua A

Dec 3, 2019

An excellent overview of Machine Learning in Python.

创建者 Jose A P L

Mar 16, 2019

Muy buen curso para iniciarse en el machine learning

创建者 Dibyendu C

Oct 17, 2018

Well structured and quality lectures and assignments

创建者 Anthony K

Jul 5, 2017

So far the course is relevant and very approachable.

创建者 Aniket K S

Aug 25, 2020

Give a lot idea about implementing machine Learning

创建者 Haozhe ( X

May 31, 2020

Great course. Love the design for each assignments.