Guided Tour of Machine Learning in Finance

This course is part of Machine Learning and Reinforcement Learning in Finance Specialization

Instructor: Igor Halperin

Skills you'll gain

  •   Regression Analysis
  •   Deep Learning
  •   Tensorflow
  •   Scikit Learn (Machine Learning Library)
  •   Reinforcement Learning
  •   Artificial Neural Networks
  •   Supervised Learning
  •   Finance
  •   Machine Learning
  •   Financial Services
  •   Applied Machine Learning
  •   Predictive Modeling
  •   Statistical Methods
  •   Jupyter
  • There are 4 modules in this course

    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.

    Mathematical Foundations of Machine Learning

    Introduction to Supervised Learning

    Supervised Learning in Finance

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