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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

6,734 個評分
1,212 條評論


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 14, 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!!


Sep 09, 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


226 - Applied Machine Learning in Python 的 250 個評論(共 1,192 個)

創建者 Andrew G

Aug 27, 2017

A lot of techniques packed into a relatively short course. Weeks 2 & 4 are noticably tougher than the other two, so allow plenty of extra time for assignment and quiz in those 2 weeks.

創建者 Tian L

Apr 20, 2020

it is a great course that covers the most important basics of the "traditional" machine learning and helps me build a solid foundation for more advanced machine learning topics later.

創建者 Alan H

May 08, 2019

Great course for the applications of machine learning. While I wouldn't recommend for someone with no ML experience, this was a great course for an R user trying to learn more python!

創建者 Rami A T

Jun 06, 2017

Very helpful and well-structured course, clear lecturing, and high-level assignments. I hope, however, if it can be offered another course specialized in unsupervised learning in ML.


May 05, 2020

Great Course. I love the way it is designed, delivered. I learned a lot. The most important part is that I enjoy every bit of the session and completed everything less than a week,

創建者 Muhammad A

Jun 08, 2018

I am just about to begins my Module 2 but I have realized that how much easy to understand and to the point course is. I would love complete it and be the proud scientist. Thanks.

創建者 Jesus P I

Apr 18, 2018

The most practical course I have completed so far. Also the right amount of theory needed to being able to start resolving your first machine learning problems. 100% recommendable

創建者 Ravi M

Feb 08, 2020

Course was designed in a well structured manner and the basic concepts were covered for Regression and Classification. Many many thanks to University of Michigan for creating it.

創建者 Gogul I

Jun 28, 2019

This is the best ever course I have taken in Coursera. Learnt very useful ML concepts that are no where available in the internet. Highly recommend this course to ML enthusiasts.

創建者 Mohamed A H

Dec 15, 2018

Awesome course!

Stick till the end of it, and you'll never regret it.

You're gonna have a lot of fun especially in the last week, don't skip the optional readings of this week ;)

創建者 Malvik P

Oct 30, 2019

The course is awesome. Professor Kevyn Collins Thompson, explains the topics with examples in python which makes content easy to understand. It is the best course for beginners.

創建者 vishy d

Aug 06, 2017

It is very good blend of study and practical assignment. Assignments were very well designed to greatly enhance the understanding about the things learned in the video lectures.

創建者 Juan D O V

Jun 15, 2020

Really good course, although it is more focused on the practical aspect I really learn much more about different machine learning techniques for improving and applying a model.

創建者 Hanbin Z

Aug 20, 2019

It is a great course. The lectures is interesting and full of knowledge. Though the assignments are challenging, especially the last one, I really learn a lot from this course.

創建者 Valeriya P

Jul 25, 2017

multi selection questions in quizzes are a bit hard to handle, i think there should be more hands-on experience included. Loved notebooks when one answer lead to the next one.

創建者 Sandilya M

Oct 25, 2020

The content is so crisp and articulated well. The assignments and quiz need fair amount of work to complete. My fav part of this course is week 4 and tutor nailed it so well.

創建者 Rob N

Oct 15, 2017

This course was challenging and extremely interesting. The long and detailed lectures and excellent lecture notes covered the material very thoroughly for an online course.

創建者 Jay S

Jul 02, 2017

Excellent introduction to Machine Learning! The course focus is on supervised ML. Well taught ! Course is well structured with lots of tips & tricks for model evaluation.

創建者 yepi

Jul 01, 2017

Great course! I have learnt a lot of machine learning skills from this course. Regression, classifier, metrics, clustering. This course cover both theory and practicing. The

創建者 Aayush N

Jul 08, 2020

A dedicated course with focus on application of supervised machine learning algorithms which can help the student to apply these algorithms in many real-world applications.

創建者 John J M

Jun 05, 2020

Feel strongly, that this is the best of the 3 core courses in the specialization. The lectures were excellent and the notebook modules supplemented the lectures very well.

創建者 GM F B M

Apr 13, 2020

This is a very first course of Machine Learning that I have ever completed. I believe, this is a very good course to understand some basic applications of ML in real life.

創建者 vipul k s

Dec 27, 2019

Really good course. The instructor taught in a very precise way. The teachings were spot on and comprehensive. After this, now I can start to work on real-life projects.

創建者 Dylan E

May 03, 2018

I enjoyed this course it was fun and very informative. This course also gave me a bunch of resources such as The Elements of Statistical Learning which is a great book!


Jul 17, 2020

ML is a wonderful course.I learn new concepts with hands on experience.Each and every algorithm concept is clearly explained .I learn how to handle real time data set.