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.
About this Course
New York University
New York University is a leading global institution for scholarship, teaching, and research. Based in New York City with campuses and sites in 14 additional major cities across the world, NYU embraces diversity among faculty, staff and students to ensure the highest caliber, most inclusive educational experience.
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TOP REVIEWS FROM FUNDAMENTALS OF MACHINE LEARNING IN FINANCE
So far so good. The lecturer refers to projects of which some weren't covered in this course. So a little confusing. Takes lots of googling to finish this course.
Furthered my understanding of how probabilistic models are connected to Machine Learning models. Very happy with the content in this course.
Great course which covers both theories as well as practical skills in the real implementations in the financial world.
This is a great course, I strongly recommend. However, the assignments take a while to finish.
About the Machine Learning and Reinforcement Learning in Finance Specialization
The main goal of this specialization is to provide the knowledge and practical skills necessary to develop a strong foundation on core paradigms and algorithms of machine learning (ML), with a particular focus on applications of ML to various practical problems in Finance.
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