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미시건 대학교의 Applied Machine Learning in Python 학습자 리뷰 및 피드백

4.6
별점
8,013개의 평가
1,460개의 리뷰

강좌 소개

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....

최상위 리뷰

AS

2020년 11월 26일

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.

OA

2017년 9월 8일

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

필터링 기준:

Applied Machine Learning in Python의 1,451개 리뷰 중 201~225

교육 기관: Farzad E

2019년 3월 14일

Assignments and quizzes help you a lot in consolidating the concepts. However, some questions in quizzes are tricky but not in a way that really adds to your understanding of the topic. Overall a pretty good course. (4.5/5 is the rating I would give)

교육 기관: CHEN S H

2021년 2월 12일

This course is well-structured and I learned a lot from it. Students who use retrieval practice, which is a form of self-testing, retain the information longer and learn better. I liked the quizzes and the assignments, and I wished there were more.

교육 기관: Amitava C

2020년 4월 18일

The course content is excellent and the instructor makes stuffs easier. Few assignments are very tough but if you go through the course properly can able to solve it. One request to the instructors to a bit slow the pace for better understanding. :)

교육 기관: 谢仑辰

2018년 3월 7일

Though it just give us a limited amount of information about Machine Learning, it really drive me into the novel world of this field.The course told me a lot of basic concepts about ML, thus I can go through many thesis related to the realm, thanks.

교육 기관: 전하림

2021년 1월 1일

Very practical lectures for implementing machine learning. Provides more hands on experience and you can get familiar with python machine learning libraries with this course. Highly recommend if you want to really practice machine learning coding.

교육 기관: H.-M. F C

2019년 1월 26일

The course ire great and illustrates many useful topics. The only thing it needs to improve is about the assignment 4 which requires more information to solve the problem, in particular, people who deal with the complete machine learning problem.

교육 기관: Olin S

2019년 1월 6일

The programming assignments where though because the automatic grader was very picky. Please change it so it gives the user more input about what part of their code is wrong. Also Have a repository where the user can retrieve previous submissions.

교육 기관: reddi m

2020년 4월 18일

Excellent course !!!!! very useful for people who have just completed python and wanted to apply the language. Much more clear when we do the course after studying the libraries of python , very clear explanation throughout the entire course .

교육 기관: Oj S

2020년 6월 1일

It was a great learning experience. The way the course structure is curated is truly adapting to the current trends in field of ML and AI. Thank you for giving me an opportunity to learn from best teachers on a great online learning platform.

교육 기관: Martin G

2020년 6월 22일

Fantastic course theory and material. Additional vague pointers would have been useful for Assignment 4 to help understand required data manipulation not included in the notebooks.

Many thanks to the team and Professor Kevyn Collins-Thompson

교육 기관: LENDRICK R

2019년 4월 7일

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. :-)

교육 기관: Dinesh M

2021년 2월 28일

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.

교육 기관: Brian R v K

2017년 10월 29일

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.

교육 기관: Yusuf E

2018년 7월 31일

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.

교육 기관: David A d A S

2017년 7월 31일

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.

교육 기관: Michael D

2017년 7월 19일

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.

교육 기관: DHANANJAY A 2

2021년 11월 23일

Excellent Course To Strengthen Your Skills In Machine Learning. Not Recommended For Beginners because It requires some amount of basic knowledge about python programming and also some basic terminologies knowledge of machine learning.

교육 기관: Vishesh G

2018년 9월 8일

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.

교육 기관: Arturo B E G

2020년 5월 31일

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

교육 기관: Ganesh K

2018년 4월 14일

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.

교육 기관: Manikant R

2020년 5월 9일

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.

교육 기관: Andrew

2019년 3월 11일

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

교육 기관: Lina J

2021년 1월 25일

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,

교육 기관: Michael L

2017년 6월 17일

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.

교육 기관: anurag s

2017년 6월 29일

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