Machine Learning for Finance · Mathematics
Practical machine learning skills in finance.
Framing the ML problem, data collection and generalization, data and loss, regularization and logistic regression, classification, natural language processing, artificial neural networks, GANs and Kmeans, and reinforcement learning.
A relatively comprehensive knowledge about all kinds of AI algorithm, including machine learning, Deep Learning and reinforcement learning.
Basic Machine Learning models and the theories behind these models
Very interesting background about the most popular machine learning algorithms
Machine learning models. Some python practices.
Different regression models including Linear, Ridge, Lasso, Elastic Net,.... Concept of gradient descent Portfolio optimization Utility of machine learning in finance
Basic ML framework, basic nlp, neutral network concepts, python technics.
The course can help you formulate machine learning skills that are practical to use.
The concepts behind lots of machine learning algorithms, and how to apply them in Python.