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Avis et commentaires pour d'étudiants pour Guided Tour of Machine Learning in Finance par New York University

529 évaluations
167 avis

À propos du cours

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....

Meilleurs avis


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.


May 28, 2018

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

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26 - 50 sur 154 Avis pour Guided Tour of Machine Learning in Finance

par Wian S

Aug 22, 2018

I absolutely love the depth that this course goes into by providing in-depth reading materials and citing advanced sources in videos for further research. Although some other reviews say that the assignments are too hard and no guidance is given, I think this is an advantage because a lot more learning goes on. I've taken other courses where all that you have to do is fill in about 10 lines of code for the entire assignment after 10 paragraphs of explanation and it really kills the learning.

par Jacques J

Nov 11, 2018

At first I was irritated that some of the material wasn't covered in class but when I read all of the recommended reading then it became more clear what to do. This course takes time and attention. Its not an introduction course, its more an an intermediate course. I was impressed with this course as it directly relates to applications in finance and helped me to see how to apply algorithms I already know to finance. It also gave me a bit more mathematical rigor.

par Wenxiao S

Feb 23, 2020

Perfect courses with challenging assignments. Together with recommended references, I learned a lot in machine learning, both about algorithms itself and applications in finance. Through the course, I finally understand ML is NOT a black box, but an optimization methods based on probability theories.

I really love such research, and I will complete the whole specialization without doubt!

par Dima S

Nov 13, 2018

I liked this course. It extends your knowledge regarding such basic algorithms as linear/logistic regression, gives some useful practice with TensorFlow. But, I would definitely recommend everyone, who didn't understand the material go through it again and read recommended materials after each week. Otherwise, such lack of understanding will be like a snowball.

par Joaquin T

Jul 18, 2018

Except for a few issues with assignment submission the course material and exposition and recommended readings were excellent. As a disclaimer, I have taken non-financial ML courses in the past, though, so I do have some background knowledge on tensorflow. That might influence my opinion.

par Vasco C

Jan 25, 2020

Excellent course, but be prepared for hard work. It's an intermediate level not an introductory course. It would be better if the assignments were better documented - it's true that we should get used to do our own research but that significantly increases the scheduled work load .

par Angelo J I T

Aug 03, 2019

While this course gets a lot of negative comments due to the inconsistencies between the exercises and the actual material, it taught me a lot about the probabilistic models behind popular machine learning algorithms. Also learning to do things in tensorflow is a great bonus.

par Felix E G L

Aug 28, 2018

This is a great course, I really learned the topics. Some people has made bad comments regarding the programming assignments difficult. But really is this difficulty what help to go deeper in the topic and conect the theory with the practice. Excelent!

par Marlon F

Dec 23, 2019

Well, the lessons are amazing. But the projects are very difficult and not so related to a better learning curve. Do a linear regression in 100 ways and thousands tools doesnt make difference. Could approach only one, but focused.

par Sudipto M

Aug 15, 2019

Really good content which is pretty focused and at the same time pretty generic. Totally perfect for someone who has python coding experience and some interest/experience in finance and ML. No prerequisites in ML/Finance required.

par Chazz E

Mar 29, 2020

The course is challenging unlike other Coursera courses, you need to learn TensorFlow if you want to pass the programming assignments. Some out of course studying was involved to complete the assignments as well.

par Juan A S

Jan 18, 2019

This course is a perfect introduction to machine learning applied to finance, which covers the essentialtopics that students must know to deepen their knowledge in this fascinating field.

par Krishna D

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.

par Eduardo C

Mar 05, 2019

Excellent! it is very wider and get to be so clear at the same time. It was an amazing experience specially because I am returning back to Coursera courses.

par Arka B

May 28, 2018

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

par Salami S A

Feb 29, 2020

The course is easy to understand and give insightful details on how to apply machine learning in finance

par David W

Sep 09, 2019

Leans heavily on explaining differences between tech and finance applications of ML, but still great!

par Swaminathan S

Mar 18, 2019

Excellent. I picked up quite a bit of ML as applied to finance through this fast paced course.

par Luis G S B

Aug 19, 2018

Audio could be better. Low recording volume makes it difficult to listen sometimes.


Nov 29, 2018

Excellent Course, Professor clases are good complement for other ML courses.

par Juan C G A

May 31, 2020

So mouch happy to take the modules, good content, good resources, Thanks


May 06, 2020

Muy buen curso aunque retador en sus trabajos de programación

par 刘晶

Oct 15, 2018

Very good course! Thank you, Professor Igor Halperin

par Pavel K

Nov 28, 2018

A very informative and well paced intro to ML / DL

par Luis A A C

Nov 15, 2018

Excellent overview of machine learning in finance