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Avis et commentaires pour l'étudiant pour Guided Tour of Machine Learning in Finance par Université de New York, Tandon School of Engineering

3.8
404 notes
124 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

KD

Aug 24, 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.

AB

May 28, 2018

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

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26 - 50 sur 111 Examens pour Guided Tour of Machine Learning in Finance

par Yuning C

Sep 08, 2018

A great course with deep insight.

par 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!

par Luis G S B

Aug 19, 2018

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

par Jacques J

Nov 11, 2018

At first I was irritated that some of the material wasn't covered in class but when I read all of the recommended reading then it became more clear what to do. This course takes time and attention. Its not an introduction course, its more an an intermediate course. I was impressed with this course as it directly relates to applications in finance and helped me to see how to apply algorithms I already know to finance. It also gave me a bit more mathematical rigor.

par Dima S

Nov 13, 2018

I liked this course. It extends your knowledge regarding such basic algorithms as linear/logistic regression, gives some useful practice with TensorFlow. But, I would definitely recommend everyone, who didn't understand the material go through it again and read recommended materials after each week. Otherwise, such lack of understanding will be like a snowball.

par Vinay P K

Nov 20, 2018

good content

par Luis A A C

Nov 15, 2018

Excellent overview of machine learning in finance

par 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.

par 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.

par Ezequiel A

Aug 07, 2018

Amazing Course!

par Jenyi L Y

Sep 18, 2018

very practical for me.

par 刘晶

Oct 15, 2018

Very good course! Thank you, Professor Igor Halperin

par hamid.zand

Jun 30, 2018

Great Course

par Arka B

May 28, 2018

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

par 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.

par 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.

par 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.

par Krishna D

Aug 24, 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.

par David W

Sep 09, 2019

Leans heavily on explaining differences between tech and finance applications of ML, but still great!

par WangFangpo

Oct 07, 2019

很好的课程。推荐的论文很值得一读。

par Mohamed H a e r

Oct 27, 2019

thanks coursera for this amazing course

par 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!

par 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

par Takayuki K

Jan 18, 2019

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

par 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.