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.
Guided Tour of Machine Learning in Finance
Guided Tour of Machine Learning in Finance
This course is part of Machine Learning and Reinforcement Learning in Finance Specialization
Instructor: Igor Halperin
36,221 already enrolled
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Gain insight into a topic and learn the fundamentals.
3.8
(674 reviews)
Intermediate level
Some related experience required
Flexible schedule
Approx. 24 hours
Learn at your own pace
83%
Most learners liked this course
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Shareable certificate
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Assessments
4 assignments
Taught in English
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This course is part of the Machine Learning and Reinforcement Learning in Finance Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
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There are 4 modules in this course
What's included
11 videos3 readings1 assignment
What's included
6 videos3 readings1 assignment1 programming assignment1 ungraded lab
What's included
7 videos4 readings1 assignment1 programming assignment1 ungraded lab
What's included
9 videos4 readings1 assignment2 programming assignments2 ungraded labs
Instructor
Instructor ratings
4.0 (77 ratings)Offered by
Recommended if you're interested in Machine Learning
New York University
New York University
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New York Institute of Finance
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3.8
674 reviews
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Showing 3 of 674
KY
4
Reviewed on Apr 17, 2021
Great overview. Please provide more code examples as homework require a lot more than what the class covers!
CO
4
Reviewed on Apr 18, 2019
Very Difficult - Impossible to succeed without very strong prior experience. Would deserve more guidelines
KD
5
Reviewed on Aug 23, 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.
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