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Big Data Applications: Machine Learning at Scale(으)로 돌아가기

Yandex의 Big Data Applications: Machine Learning at Scale 학습자 리뷰 및 피드백

86개의 평가
22개의 리뷰

강좌 소개

Machine learning is transforming the world around us. To become successful, you’d better know what kinds of problems can be solved with machine learning, and how they can be solved. Don’t know where to start? The answer is one button away. During this course you will: - Identify practical problems which can be solved with machine learning - Build, tune and apply linear models with Spark MLLib - Understand methods of text processing - Fit decision trees and boost them with ensemble learning - Construct your own recommender system. As a practical assignment, you will - build and apply linear models for classification and regression tasks; - learn how to work with texts; - automatically construct decision trees and improve their performance with ensemble learning; - finally, you will build your own recommender system! With these skills, you will be able to tackle many practical machine learning tasks. We provide the tools, you choose the place of application to make this world of machines more intelligent. Special thanks to: - Prof. Mikhail Roytberg, APT dept., MIPT, who was the initial reviewer of the project, the supervisor and mentor of half of the BigData team. He was the one, who helped to get this show on the road. - Oleg Sukhoroslov (PhD, Senior Researcher at IITP RAS), who has been teaching MapReduce, Hadoop and friends since 2008. Now he is leading the infrastructure team. - Oleg Ivchenko (PhD student APT dept., MIPT), Pavel Akhtyamov (MSc. student at APT dept., MIPT) and Vladimir Kuznetsov (Assistant at P.G. Demidov Yaroslavl State University), superbrains who have developed and now maintain the infrastructure used for practical assignments in this course. - Asya Roitberg, Eugene Baulin, Marina Sudarikova. These people never sleep to babysit this course day and night, to make your learning experience productive, smooth and exciting....
필터링 기준:

Big Data Applications: Machine Learning at Scale의 21개 리뷰 중 1~21

교육 기관: Egor M

2017년 11월 3일

Oh, that lovely accent

교육 기관: Marco G

2018년 12월 5일

The videos are good, it's just the assignments that are frustrating.

I spent at least 10 times as long trying to get them to pass the autograder as I did solving them.

You need to improve this aspect of the course if you're expecting 4 or 5-star reviews :)

교육 기관: Martin T

2018년 9월 26일

The assignments are not clear and the teacher support is poor (despit the slack channel being a welcome improvement!).

교육 기관: Nitinkumar

2020년 6월 15일

Course content is good but Quiz questions is way to different than content

교육 기관: Кряжевских С В

2020년 1월 14일

Cons outweigh the pros in this course: poor course' structure, terrible pronunciation, persistent headache in passing assignments with grader system, lack any feedback from teachers. I think this course is a loss of Yandex reputation.

교육 기관: Pramod W

2018년 5월 24일

many things was impressive

교육 기관: Egorov A

2020년 5월 7일

Perfect, thanks!

교육 기관: sekhar

2018년 3월 27일

Excellent course

교육 기관: Сергей Б

2018년 7월 8일

Course contained lots of new information for me, but exercises were too simple in comparison with other courses of specialization.

교육 기관: Alexander K

2019년 5월 23일

Nice course, but the impression about practical tasks is really awful. The tasks are ok, but grading system is too buggy

교육 기관: Paulo H C

2019년 7월 13일

Lack of clarity on how to answer questions both in quiz and programming

교육 기관: Alberto B

2018년 9월 16일

Needs more examples and to reduce the speed in many subjects.

교육 기관: Evgeniy C

2018년 9월 2일

need more simple examples and literature links

교육 기관: Rami M

2018년 8월 1일

It was good. People made lot of work on it...

교육 기관: Mykola K

2019년 8월 23일

I wish there were more practice

교육 기관: Papadopoulos K

2018년 11월 5일

The course is interesting and challenging. Some work is needed on how to best transfer the right message to the students. Some videos are going way to deep into technical details and not focusing enough on the end goal. Overall interesting and mind-engaging course.

교육 기관: Delgrange C

2019년 10월 20일

An introduction to machine learning. The transition from courses, whose concepts are easily understood with a good mathematical foundation, to practical exercises is sometimes quite difficult.

교육 기관: Samir V

2020년 9월 8일

A lot of complex math which is neither derived in lecture nor about which intuitions are provided. Equations are written on slides as if we are to just read them and remember. I am sorry for this negative review but the concepts could have been taught with more details.

교육 기관: Alexander C

2018년 9월 20일

Just a highlevel introduction to machine learning with comments like "you can also do it on spark". No details about the parallel learning process (parameter server, etc)

교육 기관: Ángel M R

2019년 1월 20일

Unexistant support, failing notebooks

교육 기관: Kirk B

2019년 1월 16일

The autograders are broken and team support is lacking. Decent lecture content however.