ICDSS Machine Learning Workshop Series: Linear Models
- Basic Linear Algebra
- Any experience with programming
The aim of this workshop is to introduce you to Data Science and especially Linear Models.
We will answer questions, such as "what is a model?" and "why linear in particular".
Then, we will go through some applications, starting with a Simple Beta Hedging algorithm, usually used in Finance.
Finally, we will get our hands dirty with implementing this algorithm in vanilla
Python and then using off-shelf Machine Learning frameworks, such as
Complete exercise task in 'Demo.ipynb' the 'notebooks' folder. Use the 'Linear Models.ipynb' notebook for guidance
Link to Binder
Finance - Simple Beta Hedging
Pythonsetup environment, according to
- Regression Analysis, MIT 18.S096 Topics in Mathematics with Applications in Finance [PDF]
- The Linear Model I, Caltech CS 156 Machine Learning [PDF]
- The Linear Model II, Caltech CS 156 Machine Learning [PDF]
- Linear Regression, Oxford Machine Learning [PDF]
- Python NumPy Tutorial, Stanford CS231n [tutorial]
- Linear Regression Example, scikit-learn [code]
- Linear Regression in TensorFlow, aymericdamien [ipynb]
- Linear Regression, Quantopian [ipynb]
- Multiple Linear Regression, Quantopian [ipynb]
- GradientDescentExample, mattnedrich [Github]
- Regression Analysis, MIT 18.S096 Topics in Mathematics with Applications in Finance [YouTube]
- The Linear Model I, Caltech CS 156 Machine Learning [YouTube]
- The Linear Model II, Caltech CS 156 Machine Learning [YouTube]
- Linear Regression, Oxford Machine Learning [YouTube]
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