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Вернуться к Guided Tour of Machine Learning in Finance

Отзывы учащихся о курсе Guided Tour of Machine Learning in Finance от партнера New York University

3.8
звезд
Оценки: 548
Рецензии: 173

О курсе

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....

Лучшие рецензии

KD
23 авг. 2019 г.

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
27 мая 2018 г.

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

Фильтр по:

126–150 из 160 отзывов о курсе Guided Tour of Machine Learning in Finance

автор: Bhushan G

19 мар. 2020 г.

D

автор: Amro T

19 мая 2019 г.

This course is more of mathematical introduction to machine learning than actual practical machine learning tips and tricks course. Math is definitely crucial but the way it was conveyed was not really good. I would have provided a refresher week just in math to refresh the students before jumping into the mathematics in the course. In the notebooks, there is a lot that was missing. Because I was already familiar with the material and I used TensorFlow, Numpy, Sklearn and statsmodels before and built several models with them before, I was able to navigate through. But if I was a totally new student, I would have a very hard time going through those notebooks. A couple of good notes, Please try to summarize all the important equations into a PDF file either for the entire course or per week to be as a reference when needed.

автор: Oliver P M

14 июля 2020 г.

The course has rather decent videos, but the actual quality of exercises dunk after the very first one. Several exercises lack vital information in order to be able to successfully complete these without resorting to guesswork, while other pure and blatantly contains errors such as resetting the random number generator when taking new batches. In addition the solutions are so airtight, that rounding errors on the smallest of decimals causes one to get zero points, while the solution in any normal circumstance would be looked at as perfectly viable. Finally the version of tensorflow used is now so old, that the documentation has been scrapped from tensorflows own webpage, resulting in certain unexpected results whenever one tries to scoure the 1.15.0 documentation for an answer to certain problems.

автор: Ricardo F

22 июля 2018 г.

I gave up while working on week 4's homework of the first course of this specialization. The two main reasons that led me to do so are: (1) very little on finance engineering except reference to problem cases and recommended readings; and (2) homework quality is really inferior to other machine learning courses I took at Coursera. I recognize that my first observation may not apply to the remaining courses of this specialization, but it is definitely the case in course 1. In the end, I thought I was not learning enough to justify the time and effort. Lectures are OK but they could be improved a lot by adding more financial engineering elements.

автор: ALI R

18 авг. 2019 г.

The course material are presented sparsely despite my initial expectation which may be formed by Andrew Ng in his ML course. Anyway I believe it is a good roadmap for learners of ML in finance and also for me to find and I should be grateful of the Coursera.

автор: Ismael A C

16 апр. 2020 г.

The course approach very interesting subject. However, it has incomplete informations and guidance throughout chapeters. I've felt much more informed by the recommended literature: Hands-On Machine Learning with Scikit-Learn & TensorFlow, by Aurélien Géron.

автор: Baoye C

1 нояб. 2020 г.

The lectures are actually very good, but I think it would help tremendously if you can make the slides and sample Jupiter notebooks used in lecture available to us. It takes us a lot of time to recreate the notebooks just to play around with them.

автор: Hrishikesh A R

23 июня 2019 г.

Objectives of assignments are not clear. The instructions provided in assignments are not clear. Tensorflow should be taught extensively because most of the students are facing problems in same.

автор: Lakshmi P

4 авг. 2020 г.

Please help me how can I submit my assignment , No submission script is active in my course as well as in my programming assignment . 6th august is my last date of my certified course .

автор: Chris M

30 июня 2018 г.

Lectures are good, but assignments are half baked, under specified and half the grading has errors. I hope this improves for people that take (and pay for!) this in the future

автор: Omar E O F

14 июня 2019 г.

Very goo lectures, but assessment exercises are not well defined. Examples not shown in lectures. Not enough briefing for starting exercises. No active forum for discussion.

автор: Vivek U

14 июля 2018 г.

Exellent content let down by endless flaws in grading system and lack of responses from tutor or instructor. Issues finally resolved 2 days before course end date.

автор: Liuyi Y

16 мар. 2020 г.

I've practiced the project before and these projects are very messily written...I would suggest MIT 6.86 as an alternative for this intro course

автор: Conan H

27 сент. 2018 г.

Interesting overview let down by lack of clarity on exercises such as the exact formulae and expected format of the outputs.

автор: Zicheng X

11 сент. 2018 г.

I faced some technique issue with submitting assignment. I hope there would be some technic help.

автор: Abhinav C

16 февр. 2020 г.

Was expecting bit more indepth. Very poor exercises with no reference to lectures. Disappointed.

автор: Simon N

1 дек. 2020 г.

No feedback from tutor in forum. Exercises confusing without much value.

автор: Quentin V

29 июля 2018 г.

The automatic grading system does not work.

автор: Sean H

31 июля 2018 г.

The material is promising, but the staff running the course do not give a lot of direction on how to pursue learning the content. The programming assignments are left almost completely to the students guessing what they're suppose to do with little direction. There is almost no feedback on how your code has performed, except to say that your code was wrong, which you already understand from not getting the points. While I was able to achieve a passing grade in this course and the next, it was only because of the community of students that figured things out together, but with no other reliable way of figuring the material out. The code was also rife with bugs that weren't fixed for weeks while students tried and failed over and over again to pass assignments that they simply could not pass. It ended up wasting many hours of my time and, no doubt, other students' time. Simply check the forums to see the frustration from the Coursera community, that normally expects and receives high quality educational content.

автор: Hoang N T

4 окт. 2018 г.

Instructions completely unclear.Variables are named term1 and term2 with no reference to which formula. Not only is this not a unique decomposition (I could write this as 4 terms or 1 term depending on the algebra), but it is terrible coding practice.Covers material and requires knowledge of things never even discussed in the course. If this is done, it should be walked through pedagogically. This is for educational purposes after all. This assignment really seems like someone just wrote a jupyter notebook going through this calculation and erased a few random lines then expected us to be able to read their minds as to what was there.

автор: Casey C

18 авг. 2018 г.

I am incredibly disappointed with this course. The subject material seems extremely interesting, and I couldn't wait to go through the course, but the graded programming assignments are terrible. They are vague to the point of impossible - the only way to pass them is to read the discussion forums and find a solution that has worked or guess and check. They cover material and techniques not even mentioned or referenced anywhere in the lectures or instructions. Worst of all, is these issues have been left unaddressed by the administrators for months despite students repeatedly voicing their concerns.

автор: Hussein H

25 янв. 2020 г.

The name of the course is what caused me to purchase, I was super excited for this course up until i reached the coding assignment. The instructions we practically not succinct whatsoever and i literally had no clue what it was asking and how to even start. From the discussions and reviews it appears alot of people have this same issue.

автор: Ehsan F

17 янв. 2020 г.

It is neither good for the beginners nor for advanced users. Specially on the finance side it's almost useless. People don't come here so you send them to read several different books. They come here so you teach them what they would find in those books. That's the actual added value and the service you are supposed to provide.

автор: Pierre C D M

14 окт. 2018 г.

The assignements do not match the content of the video therefore you are not able to test whether you understood the material or not. Basically it is better to buy the book "Hands on machine Learning" by Geron and work on Financial exam

автор: Amir T

12 апр. 2019 г.

The teaching quality is poor and lacks practical examples. It is too technical, which you don't expect for this kind of courses. The mathematics were presented poorly and sometimes without context.