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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

4.6
6,856 个评分
1,239 条评论

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

FL
Oct 13, 2017

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
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

筛选依据:

201 - Applied Machine Learning in Python 的 225 个评论(共 1,219 个)

创建者 Limber

Dec 3, 2017

It is a very practical course if you have learned the Andrew Ng's Machine Learning course. It is much much more practical and I have gained a lot from it. I really wish I could learn it soon. Thanks very much.

创建者 Ayush D

May 30, 2020

Learned a lot from this course, very informative. One thing have to say that its not for absolute beginners, this course required prior knowledge of ml and python which will ease completion of course. Thanks!

创建者 Leonid I

Oct 1, 2018

Maybe this would be difficult to implement in a time-constrained course, but it would be nice to have more insight into inner workings of various algorithms... Because otherwise this course resembles botanics.

创建者 Vibhore G

Feb 9, 2018

From this course you will learn direct application of Machine Learning using python. You can dive into the world of machine learning. Ipython notebooks used are really helpful. Learned a lot from this course.

创建者 Eunis N

May 19, 2020

This course made me learn a lot machine learning techniques by experimenting them myself. It's more than just watching the class videos and running the notebook. You need to be ready to get your hands dirty!

创建者 Yingkai

Feb 14, 2019

It is definitely the best-organized, best-paced, most-worked-on course in this specialization, and from the MOOCs I have ever taken. Strongly recommend for your knowledge and career advance. Great professor!

创建者 Tsuyoshi N

Oct 13, 2018

Excellent course. I liked the projects in this course to recap the theories that I learned in the lecture and examine the new knowledge that I learned by myself with reading python library documents online.

创建者 Alexandre M

Feb 1, 2019

Good class, and it's very nice to have the "applied" machine learning angle (as opposed to focusing on the mathematical / theoretical underpinnings, which are only important at a much later point in time)

创建者 Josh B

Feb 4, 2018

Excellent introductory course to machine learning using python. It covers the basics for the popular supervised machine learning algorithms. I'm excited to build on the knowledge this course has given me.

创建者 NoneLand

Jan 21, 2018

A very practical course for machine learning. By this course, one can get familiar with sklearn and pandas basic operation! The last assignment is a challenge for me. Thanks teacher for this great course!

创建者 Dongliang Z

Dec 21, 2017

Very good lecture for beginner:easy to understand.

Also good assignment: force you to use what you learned in the course.

The discussion forum is helpful when you meet difficulties in assignments and quiz.

创建者 Steven L

Apr 8, 2018

Very practical introduction to using Python for machine learning - less focused on theory and more focused on how to use the sklearn library and proper use cases for different classifiers and regressors.

创建者 Carlos D R

Dec 16, 2019

The course offers you a lots fot tools the face ML problems. There are few errors in the notebooks, but everyting is well documented in the forum. Good overview to represent data and train basic models.

创建者 Giorgio C

Aug 25, 2017

The course is well structured and covers all the most important topics. The programming assignment could be a bit more stimulating. Overall I'd recommend this course to everyone who's interested in ML.

创建者 Ewa L

Jun 17, 2017

Fantastic course! Great foundation on scikit-learn. Really focused on APPLYING machine learning with just enough information about the models themselves to understand what's going on behind the scenes.

创建者 Eduardo B

Jul 19, 2020

Pretty good for those who are not too familiar with all the statistics that happens "under the hood" in a machine learning algorithm. The name "applied" suits very well in that way. Congratulations!

创建者 Angelo S

Dec 20, 2018

An excellent resource to immerse yourself into machine learning methods. Professor Kevyn explains key concepts in the most intuitive way possible. It does require some previous experience in Python.

创建者 Petko S

Apr 3, 2018

Extremely useful course! You really get a lot of value from it and exactly what you would expect from such course! Very entertaining and a lot of additional educational materials! Thank You a lot!

创建者 shashank s

Aug 19, 2017

the content of videos , quiz and exercise all work extremely well together towards the stated goal of the course i.e. to give the learner a good over view of how to apply ML theories into action

创建者 Michael B

Jun 19, 2017

Not for the faint of heart and some experience with Python, in particular Pandas, is preferred. Great overview of the different methods used in machine learning. One of the better courses imo.

创建者 Brett S

Sep 18, 2020

Great content and good instruction. Need to fix the files in the assignments though. It's hard to keep track in the forums and frustrating go back and forth to find out why it's not working.

创建者 PRAKHAR K J

Apr 13, 2020

It feels good to learn something new and highly skilled demand in Engineering. Thanks to Coursera and instructor for providing such a wonderful opportunity of learning through your platform.

创建者 Jens L

Aug 20, 2018

Concise and clear presentation of the material with the majority of time focused around using TDD to learn and practice concepts through developing solutions to open ended coding challenges.

创建者 Amithabh S

Jun 23, 2017

Excellent course for someone who already has some knowledge of python but not quite familiar with machine learning. This course will teach you the application of machine learning in python.

创建者 Abdirahman A A

Jan 13, 2019

In depth course that covers a lot in a short amount of time. If you take some extra time to delve deeper into these topics, you can ensure a great overview of machine learning with python.