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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

4.6
7,024 個評分
1,278 條評論

課程概述

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....

熱門審閱

OA
2017年9月8日

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

FL
2017年10月13日

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!!

篩選依據:

201 - Applied Machine Learning in Python 的 225 個評論(共 1,258 個)

創建者 Pablo S C S

2019年8月25日

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.

創建者 Piotr K

2017年11月29日

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.

創建者 Edwin V

2020年6月17日

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.

創建者 Limber

2017年12月3日

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.

創建者 Ayush D

2020年5月30日

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!

創建者 Leonid I

2018年10月1日

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.

創建者 Andres M L

2020年12月8日

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

創建者 Vibhore G

2018年2月9日

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.

創建者 Eunis N

2020年5月19日

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!

創建者 Yingkai

2019年2月14日

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!

創建者 Tsuyoshi N

2018年10月13日

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.

創建者 Alexandre M

2019年2月1日

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)

創建者 Josh B

2018年2月4日

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.

創建者 NoneLand

2018年1月21日

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!

創建者 Dongliang Z

2017年12月21日

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.

創建者 Steven L

2018年4月8日

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.

創建者 Carlos D R

2019年12月16日

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.

創建者 Giorgio C

2017年8月25日

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.

創建者 Ewa L

2017年6月17日

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.

創建者 AMIT S

2020年11月27日

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.

創建者 Eduardo B

2020年7月19日

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!

創建者 Angelo S

2018年12月20日

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.

創建者 Petko S

2018年4月3日

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!

創建者 shashank s

2017年8月19日

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

創建者 Michael B

2017年6月19日

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.