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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
7,522 個評分
1,372 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

AS
2020年11月26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.

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!!

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201 - Applied Machine Learning in Python 的 225 個評論(共 1,355 個)

創建者 LENDRICK R

2019年4月7日

A ton of learning, a challenging & rewarding course, the final assignment incorporated concepts & techniques from the first and second courses and gave me a clearer understanding of choosing and implementing machine learning algorithms. :-)

創建者 Dinesh M

2021年2月28日

The course had the right amout of labs and lectures to experiement the different algorithms and their theory. The auto grader took a while to understand but the the discussion forum threads were immensely helpful, particularly of Sophie's.

創建者 Brian R v K

2017年10月29日

This was a great course, with broad coverage of the topic and practical application in Python with scikit-learn. Challenging quizzes were part of the learning context. Overall a great experience, and the best course in the specialization.

創建者 Yusuf E

2018年7月31日

Excellent overview of many ML algorithms. Challenging quizzes and assignments. The only downside is that some functions like fit_transform, decision_function, predict_proba could have been explained a little better. Great coverage though.

創建者 David A d A S

2017年7月31日

Awesome.

I learned a lot of fundamentals machine learning. The lectures are very clear and the assignaments focus on practical examples.

I recomend this course for everyone who want to have a global view of machine learning.

I enjoyed a lot.

創建者 Michael D

2017年7月19日

I thought this was a fascinating course that tried to do the near impossible and succinctly summarise the key techniques of machine learning. And it did that very well. Very challenging tasks, but also overall inspiring for the next step.

創建者 Vishesh G

2018年9月8日

This was an amazing course that I absolutely loved working on. It gave a deep insight into machine learning. I gained a lot of knowledge from this course. A must for the students who are just stepping in the field of Machine Learning.

創建者 Arturo B E G

2020年5月31日

It's a nice course, that accomplishes what it promised: overviewing ML algorithms from an applied perspective; however, I think that some other model selection methods (especially when comparing regressions) should have been included

創建者 Ganesh K

2018年4月14日

Tough and exhausting, but thoroughly worth it. I learnt a lot - and I already knew machine learning before taking this course. Be prepared to spend a lot of time preparing for the quizzes. The assignments are easier than the quizzes.

創建者 Manikant R

2020年5月9日

The course is well taught, by covering a lot of topics in short time, Yes you have to research a lot to get a full understanding, as the ML itself is not easy, you have to do hard work. I liked the references provided in the course.

創建者 Andrew

2019年3月11日

Really well explained theory without too much of a mathematical deep dive that provides a perfect set up to learn about machine learning from a purely math/stats perspective through Andrew Ng's Machine Learning course or self study

創建者 Lina J

2021年1月25日

That was a great and challenging course.

I am glad I took it, I learned a lot from the videos and especially from the labs. The last lab took me 5 days to figure out while I was benefit a lot from succeeding in coding it.

Thank you,

創建者 Michael L

2017年6月17日

Excellent high level advance course with in depth explanations. It is well structured. It learn me to applied Machine learning from very basics to optimum level. It help me to understand details of Machine Learning in Python.

創建者 anurag s

2017年6月29日

Clear, smooth and awesome course. Had fun learning the theoretical stuffs . Assignments and quizzes are really helpful in understanding the concepts. Last assignment helped a lot in applying the things learned in this course

創建者 Shreyas M T

2018年9月22日

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.

創建者 atul s

2020年5月21日

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.

創建者 Daniel N

2017年7月10日

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.

創建者 Mohamed H

2018年6月26日

C'est le meilleure cours en pratique que j'ai rencontré dans toute ma vie.je 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.

創建者 Dennis W

2020年6月7日

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.

創建者 Ashish C

2019年11月29日

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.

創建者 MARKANTI B S

2020年8月14日

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

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 Abhay S

2021年2月4日

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.

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.