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Guided Tour of Machine Learning in Finance(으)로 돌아가기

뉴욕 대학교 공과 대학의 Guided Tour of Machine Learning in Finance 학습자 리뷰 및 피드백

3.8
359개의 평가
113개의 리뷰

강좌 소개

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....

최상위 리뷰

AB

May 28, 2018

Exceptional disposition and lucid explanations! Ideal for a Risk Management professional to sharpen machine learning skills!

SS

Mar 18, 2019

Excellent. I picked up quite a bit of ML as applied to finance through this fast paced course.

필터링 기준:

Guided Tour of Machine Learning in Finance의 101개 리뷰 중 26~50

교육 기관: Eduardo C

Mar 05, 2019

Excellent! it is very wider and get to be so clear at the same time. It was an amazing experience specially because I am returning back to Coursera courses.

교육 기관: Swaminathan S

Mar 18, 2019

Excellent. I picked up quite a bit of ML as applied to finance through this fast paced course.

교육 기관: Luis A A C

Nov 15, 2018

Excellent overview of machine learning in finance

교육 기관: Yangtao W

Dec 02, 2018

very good course!!!

교육 기관: Ezequiel A

Aug 07, 2018

Amazing Course!

교육 기관: Joaquin T

Jul 18, 2018

Except for a few issues with assignment submission the course material and exposition and recommended readings were excellent. As a disclaimer, I have taken non-financial ML courses in the past, though, so I do have some background knowledge on tensorflow. That might influence my opinion.

교육 기관: Wian S

Aug 22, 2018

I absolutely love the depth that this course goes into by providing in-depth reading materials and citing advanced sources in videos for further research. Although some other reviews say that the assignments are too hard and no guidance is given, I think this is an advantage because a lot more learning goes on. I've taken other courses where all that you have to do is fill in about 10 lines of code for the entire assignment after 10 paragraphs of explanation and it really kills the learning.

교육 기관: Yuning C

Sep 08, 2018

A great course with deep insight.

교육 기관: 刘晶

Oct 15, 2018

Very good course! Thank you, Professor Igor Halperin

교육 기관: Luis G S B

Aug 19, 2018

Audio could be better. Low recording volume makes it difficult to listen sometimes.

교육 기관: Jenyi L Y

Sep 18, 2018

very practical for me.

교육 기관: Felix E G L

Aug 28, 2018

This is a great course, I really learned the topics. Some people has made bad comments regarding the programming assignments difficult. But really is this difficulty what help to go deeper in the topic and conect the theory with the practice. Excelent!

교육 기관: Jong H S

Jul 27, 2018

This is an excellent course bringing together machine learning and finance. The content and exercises are just nice as introduction to both subjects. The clarity of contents presented in relating these 2 are timely and commendable. The Jupyter notebooks were a little buggy with some annoying glitches in the beginning but things are all ok. The descriptions in Jupyter on what the students need to achieve probably need a bit of polish. Overall a 5-star. Great job to Professor Halperin and team.

교육 기관: Arka B

May 28, 2018

Exceptional disposition and lucid explanations! Ideal for a Risk Management professional to sharpen machine learning skills!

교육 기관: hamid.zand

Jun 30, 2018

Great Course

교육 기관: Angelo J I T

Aug 03, 2019

While this course gets a lot of negative comments due to the inconsistencies between the exercises and the actual material, it taught me a lot about the probabilistic models behind popular machine learning algorithms. Also learning to do things in tensorflow is a great bonus.

교육 기관: Sudipto M

Aug 15, 2019

Really good content which is pretty focused and at the same time pretty generic. Totally perfect for someone who has python coding experience and some interest/experience in finance and ML. No prerequisites in ML/Finance required.

교육 기관: Pedro M H V

Dec 06, 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.

교육 기관: Mihails S

Jan 01, 2019

Despite all the problems with the assignments and the grader this course provides really good overview ML tools and their application to finance. It's definitely worth the effort

교육 기관: Takayuki K

Jan 18, 2019

One of assignments was hard. Explanation by lecturer was very easy to understand and appropriate long.

교육 기관: Hashim M

Dec 29, 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!

교육 기관: Xu Z

Aug 01, 2018

The course content is a mix of theory and practical stuff. One star off is due to the poor quality of programming assignment, i.e., unclear instructions and explanations.

교육 기관: Manimaran P

Aug 11, 2018

The Lectures and given readings are very useful and it is required to read them to complete the assignments which will otherwise be difficult

교육 기관: Bozanian K

Aug 14, 2018

Very interesting course. Covers the main algorithms of supervised machine learning and their applications to the world of finance. The one and only down is that programming session are a little hard to understand

교육 기관: Russell H

Sep 01, 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).