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Avis et commentaires pour d'étudiants pour Guided Tour of Machine Learning in Finance par New York University

3.8
étoiles
611 évaluations
197 avis

À propos du cours

This course aims at providing an introductory and broad overview of the field of ML with the focus on applications on Finance. Supervised Machine Learning methods are used in the capstone project to predict bank closures. Simultaneously, while this course can be taken as a separate course, it serves as a preview of topics that are covered in more details in subsequent modules of the specialization Machine Learning and Reinforcement Learning in Finance. The goal of Guided Tour of Machine Learning in Finance is to get a sense of what Machine Learning is, what it is for and in how many different financial problems it can be applied to. The course is designed for three categories of students: Practitioners working at financial institutions such as banks, asset management firms or hedge funds Individuals interested in applications of ML for personal day trading Current full-time students pursuing a degree in Finance, Statistics, Computer Science, Mathematics, Physics, Engineering or other related disciplines who want to learn about practical applications of ML in Finance Experience with Python (including numpy, pandas, and IPython/Jupyter notebooks), linear algebra, basic probability theory and basic calculus is necessary to complete assignments in this course....

Meilleurs avis

LP
22 oct. 2021

Very useful course. Personally, I think that there should have been more focus on the implementation of tensorflow and neural network codes. Overall the course is well structured and very clear.

KD
23 août 2019

Introduction of ML for Financial application with combination of Scikit learn, Statsmodels and Tensorflow with neuralnets made this class very interesting. Learned and Enjoyed lot.

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51 - 75 sur 184 Avis pour Guided Tour of Machine Learning in Finance

par EDGAR H M

6 mai 2020

Muy buen curso aunque retador en sus trabajos de programación

par 刘晶

15 oct. 2018

Very good course! Thank you, Professor Igor Halperin

par Pavel K

28 nov. 2018

A very informative and well paced intro to ML / DL

par Luis A

15 nov. 2018

Excellent overview of machine learning in finance

par Sileye B

21 déc. 2020

I enjoyed thi introduction to ML for finance.

par mohamed h

27 oct. 2019

thanks coursera for this amazing course

par Yergali B

4 janv. 2019

Thank you, for this very useful course!

par Daria

15 mai 2020

Great introduction to ML in Finance!

par Vilimir Y

2 mars 2020

A great course by a great lecturer!

par Yuning C

8 sept. 2018

A great course with deep insight.

par Muntu M

18 janv. 2020

Excellent Course, Well presented

par Sreenath P K

5 avr. 2020

Very well taught course!

par Jenyi L Y

17 sept. 2018

very practical for me.

par Yangtao W

2 déc. 2018

very good course!!!

par WangFangpo

7 oct. 2019

很好的课程。推荐的论文很值得一读。

par Ezequiel A G

7 août 2018

Amazing Course!

par LiengPhu T

15 janv. 2021

Verry good !

par Vinay P K

20 nov. 2018

good content

par hamid.zand

30 juin 2018

Great Course

par Sam

31 oct. 2021

Thank you!

par Russell H

1 sept. 2018

Good overview of ML in Finance, clearly based on real-world experience. Would not recommend this as a first ML course; probably more useful after first taking another more general course, such as Guestrin's UW ML specialization. Some of the quizzes and exercises seem a bit rushed; e.g., out of order vs. the lectures and not clear about what is required. It was sometimes necessary to consult the discussion forums for clarification. The most useful part may be the categorization of ML algorithms along different axes, including applicability to different areas of finance. The readings and coding exercises seem to come mostly from Geron's O'Reilly book, so plan on buying that (it's a great book, so you should buy it whether you take this course or not).

par Benny P

6 déc. 2019

This course has been informative, and extremely FUN! This is not to say that it's perfect, in fact as others say the assignments are quite challenging because there's little introduction to the problem/solution being asked. But that's exactly where the fun is! You need to search for the information yourself to solve the problem, much like in the real world. In fact I took another course on TensorFlow in the middle of this course to finish the assignment. But I can imagine this would be frustrating for those with less background on ML or programming, or people who expect everything to be presented smoothly for them.

par Hashim M

29 déc. 2018

A much needed course by a very seasoned expert in the field, bringing the right blend of backgrounds in finance and tech. The course is well designed for finance professionals with some coding background and for technology professionals with some finance background - which is unique in that sense. Some bridging between lectures and assignments is needed but that kind of fine tuning is inevitable and as more students enroll, the discussion rooms and feedback will provide that sharpening at the edges organically. All in all, I enjoyed the course a lot and look forward to the next three in the specialization!

par gareth o

24 sept. 2020

Lectures are very good and the use of financial examples really brings the subject alive. However the final projects are not very closely linked to the material taught, it's possible to pass if you ignore the new material. It would also be nice to update the tensorflow code from 1.0 to 2.0 as it would make things much easier to debug.

par Pedro H

6 déc. 2018

Potentially great course with bridges technology (machine learning methods) and application (finance), but as for now it is really rough around the edges. Still needs to improve in terms of video lectures, resources and assignments; but once polished it could be a great course/specialization.