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

3.8
Sterne
526 Bewertungen
166 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

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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76 - 100 von 153 Bewertungen für Guided Tour of Machine Learning in Finance

von Maksim G

Jun 10, 2019

Good material but assignments explanation were too sparse and even expectation of material not covered in videos or readings (example is Tobit regression in week 4).

von Aydar A

May 24, 2019

To much math in lectures, assignments are not coherent and complicated, im not sure that i need tensorflow from scratch to work with finance(Keras fits better)

von Hongsun K

Jan 18, 2020

Great general overview of machine learning. I think the course can be re-organized to incorporate some of the theory and some coding tips as well, however.

von 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

von Chad W L

Jul 12, 2018

This will be a 5 star course when all of the technical issues are resolved. More timely feedback from the staff is desirable as well.

von Ishrit T

Jun 16, 2019

A more detailed introduction and guide to python for machine learning would have made this course one of the best out there

von Julien T

Sep 17, 2018

Very interesting content well delivered, the programming assignments could benefit from a little more guidance IMHO.

von Songjie H

Jul 03, 2020

Homework is not always consistent with what's covered in class. The recommended readings are very helpful.

von Takayuki K

Jan 18, 2019

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

von Amalka W

Sep 13, 2018

It would be great the background theory of related concept are explained in optional videos.

von Zoraiz A

Jul 13, 2020

Later assignmnets were difficult but lecture material is interesting and well taught.

von Rafael D d D

May 02, 2020

Very good review and selected topics, although I would deep more on tensorflow use

von Zheng W

Sep 22, 2018

The course content is okay, but the programming assignments are not well designed.

von Mohammed B

Feb 02, 2020

Great course, but the coding projects are sometime hard to understand

von Gayatri L

Feb 07, 2020

Learned ML concepts and algorithms to be used in financial work.

von Edward W

Jul 26, 2020

Would be cool if was update to use latest version of tensorflow

von Noordeen m

Jun 23, 2019

was good but expect alitle explanation on the finance stuff

von Raphael R C

Jul 05, 2020

Exercises need better explanations and code

von 徐晓彬

Jun 25, 2018

The projects are not so understood.

von Wei-Chun K

Apr 27, 2020

The grading system isn't good.

von Alexander R

Oct 17, 2018

Assignments were whack...

von Kevin C N

Apr 26, 2020

Great Course!

von Roland E

Jan 09, 2020

The assignments and project are very briefly explained. It took me a lot of unnecessary time to figure out what I was supposed to do. Also the discussion forum is inactive and I have a feeling many leave after seeing not anyone respond to their questions. I think there should be one or two dedicated support answering questions at least within 3 days.

The level of the course in general is pretty high, definitely not beginners level, which is fine I guess, but I do find the lectures are at times going very quick and at times overcomplicate. I would prefer an example to start simple and from there to build for a more complex situation. (For example start the bank failure with say 3 main features and show how you can decide to add another one by showing its impact through deviance and multicollinearity and show how you can then decide to add this new feature or not.)

von Fabien N

Jan 12, 2020

Actually I was finding that course amazing at first, but I gradually became very upset. The notebooks are way too high level and not self-explanatory. The teacher seems amazing by his knowledge, but one are left with the notebooks without knowing what to do, and the lectures only partially help to solve the problems. A lot of search online needs to be done and I don't think that is the spirit of Coursera courses. I was planning to pay for the whole specialization but unfortunately I will have to give up on this course that was very motivating at first...

von Luis S M

Mar 29, 2020

The lectures, as well as the quizzes, are great and coherent. However, the practical assignments, which are supposed to be the moment of cross-checking your level of comprehension of the learned topics are rather frustrating. I believe it would be of great help to future course takers to clearly state your expectations (e.g. through more detailed exercise descriptions) and introducing vital concepts before requiring their use.