https://github.com/kavaivaleri/machine-learning-assignment

This is a code for a final assignment project during my undergraduate course on machine learning. It covers topics like Bayesian inference, regularization, gradient descent. The code was written by me and my colleague Daria.
https://github.com/kavaivaleri/machine-learning-assignment

bayesian-inference gaussian-processes gradient-descent kernels network neural regularization

Last synced: about 4 hours ago
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This is a code for a final assignment project during my undergraduate course on machine learning. It covers topics like Bayesian inference, regularization, gradient descent. The code was written by me and my colleague Daria.

• Host: GitHub
• URL: https://github.com/kavaivaleri/machine-learning-assignment
• Owner: kavaivaleri
• Created: 2021-03-26T07:33:31.000Z (over 3 years ago)
• Default Branch: main
• Last Pushed: 2021-06-16T08:27:46.000Z (over 3 years ago)
• Last Synced: 2023-08-18T08:21:30.463Z (over 1 year ago)
• Topics: bayesian-inference, gaussian-processes, gradient-descent, kernels, network, neural, regularization
• Language: Jupyter Notebook
• Homepage:
• Size: 2.05 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
Machine learning assignment includes several excercises made by me and my collegue:

- Exercise 1: Bayesian inference for the mean of Gaussian distribution

- Exercise 2: Regularized regression

- Exercise 3: Gradient descent

- Exercise 4: Gaussian process and kernels

- Exercise 5: Neural networks

Each exercise includes several questions on deriving formulas, implementing these formulas using Python and plotting the results. We also provide the interpretations of our results.