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FYS-STK4155 - Applied Data Analysis and Machine Learning

Project 1

Description of the project is available here: Project 1 PDF

Project 2

Description of the project is available here: Project 2 PDF

Project structure

In the project2 folder you will find report/ and src/, where report/ contains the .tex and pdf of the final report, and src/ contains the code. requirements.txt contains all needed packages to run all the python code in this project.

src/

Within the src/ folder you will find the following:
├── src
│   ├── data
│   ├── ising_data.py
│   ├── lasso.py
│   ├── logistic.py
│   ├── neural_net
│   ├── ols.py
│   ├── project2.py
│   ├── resampling.py
│   ├── ridge.py
│   ├── task_ab.py
│   └── task_c.py

The data/ folder contains all the Ising model datafiles provided by Mehta et al here: Notebooks and data
The files in the src/ folder contain classes with regression methods with the same name.
E.g ols.py -> orinary least squares, logistic.py -> logistic regression.
Exceptions to this are the following files:

├── ising_data.py (Generates 1D Ising data)
├── task_ab.py (Produces results for task a and b in the project description)
└── task_c.py (Produces results for task c in the project description)

The neural_net/ folder contains all the files relevant to the neural network.
├── neural_net
│   ├── network_testing.py (Deprecated)
│   ├── neural_net.py (Object-oriented implementation of the network)
│   └── run_network.py (Imports Ising data and runs the network)

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Exercises and projects for Applied Data Analysis and Machine Learning

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