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学生对 New York Institute of Finance 提供的 Using Machine Learning in Trading and Finance 的评价和反馈

3.9
378 个评分

课程概述

This course provides the foundation for developing advanced trading strategies using machine learning techniques. In this course, you’ll review the key components that are common to every trading strategy, no matter how complex. You’ll be introduced to multiple trading strategies including quantitative trading, pairs trading, and momentum trading. By the end of the course, you will be able to design basic quantitative trading strategies, build machine learning models using Keras and TensorFlow, build a pair trading strategy prediction model and back test it, and build a momentum-based trading model and back test it. To be successful in this course, you should have advanced competency in Python programming and familiarity with pertinent libraries for machine learning, such as Scikit-Learn, StatsModels, and Pandas. Experience with SQL is recommended. You should have a background in statistics (expected values and standard deviation, Gaussian distributions, higher moments, probability, linear regressions) and foundational knowledge of financial markets (equities, bonds, derivatives, market structure, hedging)....

热门审阅

GC

Apr 9, 2020

Very Good! Basic strategies explored in depth and applied in coding labs.

NS

Jan 26, 2020

I enjoyed the course. Well organized, Good topics.I miss more projects, higher challenge in the projects. (more TODO)There was no practice of Kalman filters.links on the slides are not accessible :-(

筛选依据:

101 - Using Machine Learning in Trading and Finance 的 116 个评论(共 116 个)

创建者 Andrey R

Jan 18, 2025

Absolutely irrelevant and outdated content. None of instructions are reflecting current state of Google Cloud. Google Cloud is absolutely unnecessary for the course and could be easily replaced by a local Jupyter notebook. Notebooks provided produce errors and warnings in almost every cell. The course is really bad. The only reason I stayed was the guy from New York Institute of Finance who talks very basic but very usefull stuff.

创建者 Chris C

Mar 16, 2021

I understand that this course is not about building the world's best high frequency trading model. On the other hand, it should at least be about making a serious attempt to build a trading model, which is something the series of courses has so far neglected to even attempt.

创建者 Brendan K

Jul 25, 2022

You should stop offering this course if you are not going to fix that Auquan no longer works. The code fix you suggested for the Yahoo Finance changes no longer works. Please see the discussion boards because this is true for many people.

创建者 masoud g

Feb 16, 2021

It was not as practical as I thought.

In this course, complete contents are not expressed and it is necessary to search for topics.

Access to the lab is difficult to code. And coding exercises are not purposeful

创建者 Andrew H

Apr 19, 2020

Needs actual exercises. All of the programming examples are pre-written or copy/paste. No real hand on learning opportunities.

创建者 Tobias M

Mar 14, 2026

I've taken many courses on Coursera, but I regret to say that this one is by far the worst.

创建者 IOANNIS P

Mar 12, 2025

some of the code won't run, and some instructions are outdated (AI Platform vs Vertex AI)

创建者 Javier M

Jul 10, 2024

Google Cloud Content is outdated, instructions are all wrong.

创建者 Vinayak T

Sep 3, 2021

This is a commercial for using the Google cloud platform.

创建者 Noviyanti K

Jun 26, 2020

idk why the code on notebook always get error

创建者 Russell K

Jun 18, 2020

almost nothing to do with machine learning

创建者 Philipp L

Mar 6, 2024

Notebooks are outdated and don't run!

创建者 William L

May 25, 2022

terrible enviroment settings

创建者 KG

Apr 9, 2024

lab 3 and 4 don't work

创建者 Deleted A

Nov 10, 2022

Labs Malfunction

创建者 Alexander R

Jun 7, 2020

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