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Learner Reviews & Feedback for Fundamentals of Machine Learning in Finance by New York University

3.7
stars
336 ratings

About the Course

The course aims at helping students to be able to solve practical ML-amenable problems that they may encounter in real life that include: (1)
understanding where the problem one faces lands on a general landscape of available ML methods, (2) understanding which particular ML
approach(es) would be most appropriate for resolving the problem, and (3) ability to successfully implement a solution, and assess its
performance. A learner with some or no previous knowledge of Machine Learning (ML) will get to know main algorithms of Supervised and
Unsupervised Learning, and Reinforcement Learning, and will be able to use ML open source Python packages to design, test...
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Top reviews

LA

Jan 6, 2019

Excellent course. I only wish to have had programming assignment with RNN and Hidden Markov Models instead of three assignments on PCA. Although they highlighted a interesting application in finance.

AT

Aug 9, 2019

Furthered my understanding of how probabilistic models are connected to Machine Learning models. Very happy with the content in this course.

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76 - 80 of 80 Reviews for Fundamentals of Machine Learning in Finance

By Chaofan S

•

Mar 19, 2020

The assignment is not related to the contents and has bugs that no one responds.

By Arnav S

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Mar 17, 2020

Too bland. Reading off the slides. Couldn't understand anything.

By Ehsan F

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Feb 27, 2020

one of the worst courses I took in Coursera

By Ivan G

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Apr 2, 2024

Peer review for lab is a poor idea.

By Wolfy G

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Nov 13, 2022

Lab issue not fixed