Machine Learning for Finance and Economics

Université Panthéon-Assas, Paris II

Instructor: Amir Sani (

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Course Details

This is an applied course in Machine Learning intended for students of Economics and Finance. Course contents will be posted before each class.

Programming Language:

The official language of this course is Python 3. We will use Anaconda in class.

You are expected to know how to program in Python before taking this class.


Grades will be based on individual quizzes and a team project.


The following materials are useful for the course:
- The Elements of Statistical Learning: Data Mining, Inference and Prediction, Python Notebooks
- Applied Predictive Modeling
- Probability Theory Review
- Linear Algebra Review

Course Schedule

Class 1: Foundation

Class Notebooks:



For a more theoretical treatment, see:

Class 2: Feature Selection

Class Notebook:


Class 3: Algorithms and Analysis

By the end of this class, you should have setup a basic submission for the Kaggle challenge.

Class Notebook:


Class 4: Model Selection and Evaluation

Class Notebook:


Class 5: Final Submissions

  • Quiz 5
  • Final Kaggle submission due on Kaggle and as Python Notebook (this is your team project) at 10h00
  • Kaggle competition (class) leaderboard review at 11h00

Please submit your final project notebook via email (to and complete this Final Project submission form.