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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

7,141 个评分
1,296 条评论


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....


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!!

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.


201 - Applied Machine Learning in Python 的 225 个评论(共 1,275 个)

创建者 Shreyas M T

Sep 22, 2018

Everything builds up very nicely on top of each other. A qualm some might have is that part of the assessments might be very simple. However, this is an applied course and the course material stays true to what it promises.

创建者 atul s

May 21, 2020

Making ML concepts accessible to the general public. If you are interested in gaining a basic understanding of the broad field, dive right in. Final assignment of Week 4 will really test all you have learned in the course.

创建者 Daniel N

Jul 10, 2017

I think this course is a real challenge and gives a great introduction to machine learning. I enjoyed it

thoroughly even if I had my troubles with the Quiz questions.. Great course overall, I would recommend it to anyone.

创建者 Mohamed H

Jun 26, 2018

C'est le meilleure cours en pratique que j'ai rencontré dans toute ma vous remercie énormément pour m'offrir cette cours et je remercié mon professeur pour la simplicité et la méthode avec laquelle a fait ce cours.

创建者 Dennis W

Jun 7, 2020

Absolutely must take for hands-on experience and practical knowledge. Instructor explained the tough course material in easy to grasp way. The assignments are challenging but achievable with time and reinforce learning.

创建者 Ashish C

Nov 29, 2019

This is the best course for machine learning. Assignments are really good. It make sure you know all the things that are taught to you. Even some times I had to go through the lectures again to complete the assignment.


Aug 14, 2020

This is one of best machine learning course among I did . It about how to apply machine learning alogrithms rather than explaination how alogrithms works but a brief idea is given about that machine learning alogrithm

创建者 Pablo S C S

Aug 25, 2019

This course was a very very good introduction to ML focusing on SciKitLearn and using many real-life examples and datasets. Prof. Kevyn Thompson is very engaging and professional. I don't know how it could be better.

创建者 Abhay S

Feb 4, 2021

A great high-level overview course on machine learning. Great challenging assignments and highly conceptual. Putting everything together, building intuitions on different topics that one can leverage for lifetime.

创建者 Piotr K

Nov 29, 2017

Great course to gain basic ML skills and start building first models. Excellent starting point. Combined with Andrew Ng`s course on Machine Learning it`s great foundation for futher development as AI specialist.

创建者 Edwin V

Jun 17, 2020

Machine Learning Fundamentals are taught in concise and easy to understand manner. Some of the ML algorithms such as Kernelized SVM have been explained brilliantly. Thanks for putting up this wonderful course.

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 Andres M L

Dec 8, 2020

I loved the course. The explanations are simple and full of day to day life examples. The final assignment was based on a real world problem, showing how the concepts can be applied not just in a play dataset

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 20, 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.