100DaysofMLCode
machine_learning_basics
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MIT License | MIT License |
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100DaysofMLCode
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#100DaysofMLCode Challenge
NishkarshRaj / 100DaysofMLCode
machine_learning_basics
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Bayesian linear regression in (plain) Python
A while back I open sourced a repository implementing fundamental machine learning algorithms in Python, along with the most important theoretical information. I originally created the repository for myself when preparing for AI residency interviews. You can find the original Reddit post here.
- Bayesian linear regression in Python
What are some alternatives?
100-Days-Of-ML-Code - 100 Days of ML Coding
Financial-Models-Numerical-Methods - Collection of notebooks about quantitative finance, with interactive python code.
hdbscan - A high performance implementation of HDBSCAN clustering.
rmi - A learned index structure
borb-google-colab-examples - This repository contains some examples of using borb in google colab. These examples enable you to try out the features of borb without installing it on your system. They also ensure the system requirements and imports are all taken care of.
rtdl - Research on Tabular Deep Learning (Python package & papers) [Moved to: https://github.com/Yura52/rtdl]
mango - Parallel Hyperparameter Tuning in Python
vqgan-clip-generator - Implements VQGAN+CLIP for image and video generation, and style transfers, based on text and image prompts. Emphasis on ease-of-use, documentation, and smooth video creation.
trulens - Evaluation and Tracking for LLM Experiments
notebooks - Implement, demonstrate, reproduce and extend the results of the Risk articles 'Differential Machine Learning' (2020) and 'PCA with a Difference' (2021) by Huge and Savine, and cover implementation details left out from the papers.