https://github.com/turkunov/ml-from-scratch

Thoroughly documented implementations of ML and DS concepts
https://github.com/turkunov/ml-from-scratch

ds implementation interview ml pytorch tutorial

Last synced: about 1 month ago
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Thoroughly documented implementations of ML and DS concepts

• Host: GitHub
• URL: https://github.com/turkunov/ml-from-scratch
• Owner: turkunov
• License: mit
• Created: 2023-11-21T19:57:51.000Z (about 1 year ago)
• Default Branch: main
• Last Pushed: 2024-06-27T14:34:34.000Z (6 months ago)
• Last Synced: 2024-06-27T17:44:43.773Z (6 months ago)
• Topics: ds, implementation, interview, ml, pytorch, tutorial
• Language: Jupyter Notebook
• Homepage:
• Size: 20.5 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# ml-from-scratch

### **TL;DR**

This repository showcases my learning journey in the world of DS and ML. It is also meant to publicly share comprehensive and reproducible examples written in Python that are supported by digested theory collected through **hundreds** of different sources. Currently here you can find detailed information on: 

- classic ML (supervised and unsupervised)

- dl (different DL architectures in PyTorch)

- ds (A/B testing: frequentist and bayesian approaches)

- linalg (linear algebra concepts: svd, pca, fft (and everything signal-related), t-SNE)

- misc (common ML problems, that you are asked about on interviews, as well as approaches to them)

Tech stack: pytorch, torchvision, polars, wandb, scikit-learn, numpy, scipy, plotly