https://github.com/pklatka/elements-of-statistical-ml-course

Solutions for elements of statistical machine learning course at AGH UST.
https://github.com/pklatka/elements-of-statistical-ml-course

Last synced: 8 days ago
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Solutions for elements of statistical machine learning course at AGH UST.

• Host: GitHub
• URL: https://github.com/pklatka/elements-of-statistical-ml-course
• Owner: pklatka
• Created: 2023-03-19T22:29:05.000Z (almost 2 years ago)
• Default Branch: main
• Last Pushed: 2023-10-03T08:28:42.000Z (over 1 year ago)
• Last Synced: 2023-10-03T19:59:49.383Z (over 1 year ago)
• Language: Jupyter Notebook
• Size: 5.54 MB
• Stars: 0
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Elements of statistical machine learning course

This repository contains solutions for elements of statistical machine learning course at AGH UST. Every task is in a separate folder. Solutions were written using Python.

## Tasks

- [lab1](https://github.com/pklatka/elements-of-statistical-ml-course/tree/main/lab01.ipynb): Monte Carlo introduction to Python, NumPy and Jupyter notebooks

- [lab2](https://github.com/pklatka/elements-of-statistical-ml-course/tree/main/lab02.ipynb): Estimating object location from noisy radar echos

- [lab3](https://github.com/pklatka/elements-of-statistical-ml-course/tree/main/lab03.ipynb): Linear regression

- [lab4](https://github.com/pklatka/elements-of-statistical-ml-course/tree/main/lab04.ipynb): Gaussian Process Regression

- [lab5](https://github.com/pklatka/elements-of-statistical-ml-course/tree/main/lab05.ipynb): Logistic regression

- [lab6](https://github.com/pklatka/elements-of-statistical-ml-course/tree/main/lab06.ipynb): Introduction to Tensorflow and Tensorflow Probability

- [lab7](https://github.com/pklatka/elements-of-statistical-ml-course/tree/main/lab07.ipynb): MCMC Inference in Hierarchical Bayesian Models

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