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Kursteilnehmer-Bewertung und -Feedback für Guided Tour of Machine Learning in Finance von New York University Tandon School of Engineering

3.8
359 Bewertungen
113 Bewertungen

Über den Kurs

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....

Top-Bewertungen

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.

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76 - 100 von 102 Bewertungen für Guided Tour of Machine Learning in Finance

von Shobhit L

Aug 06, 2018

The assignments can improve a lot. The jupyter notebooks have no clarity in instructions and most of the time we have to struggle to find exactly what is expected from our code.

The specialization has a lot of potential, anchored only by the lack of the quality of the assignments.

von Desi I

Sep 18, 2018

Good overview of ML and some basic applications to finance.

The pace is very good for people with some training in statistics and maths.

The assignments, however, are not particularly clear and with some obvious errors. There's room for improvement in the description of the exercises as well as including some tests to verify that you're getting the correct output.

von Ruixin Y

Jun 18, 2018

Spent more time than expected. And when I tried to access the last assignment, it showed "404 : Not Found You are requesting a page that does not exist!"I understand the professor and other TA put a lot of effort on these courses, but I would say the assignments are not well organized, and more instructions are needed. Really hope the instructors could update/improve the courses/assignments. Thanks.

von Alan X

Jul 29, 2018

There is always something to be fixed in the assignments... Great content and relevance though.

von Vivek U

Jul 14, 2018

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.

von Leo s

Sep 12, 2018

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

von Conan H

Sep 27, 2018

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

von Ricardo F

Jul 22, 2018

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.

von Chris M

Jul 01, 2018

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

von Quentin V

Jul 29, 2018

The automatic grading system does not work.

von Omar E O F

Jun 14, 2019

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.

von Amro T

May 19, 2019

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.

von Hrishikesh A R

Jun 23, 2019

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.

von ALI R

Aug 19, 2019

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.

von Amir T

Apr 12, 2019

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.

von Alberto G C

Sep 10, 2018

Assignments are very poorly explained and not always related to the lessons

von Matthieu B

Aug 31, 2018

A guided tour with too many shortcomings and errors assessments.

von Casey C

Aug 19, 2018

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.

von Hoang N T

Oct 04, 2018

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.

von Andreas A

Nov 21, 2018

Horrible labs

von Deleted A

Jul 31, 2018

The course content is okay but the assignments are so poorly designed and no one responds to the questions on Week3 assignment #5.

von Sean H

Jul 31, 2018

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.

von Boris S

Aug 21, 2018

Totally useless course. The professor has no idea how to teach. I recommend to take a good course in machine learning and a good course in finance instead this one.

von Pierre C D M

Oct 14, 2018

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

von wasif.masood

Sep 06, 2018

This guys uses so difficult language to explain which to me looks like as if he himself does not really know what he is teaching. This is really annoying. The course outline is good though.