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books

machine learning books

coursera-machine-learning-engineering-for-prod-mlops-specialization

Programming assignments and quizzes from all courses within the Machine Learning Engineering for Production (MLOps) specialization offered by deeplearning.ai

data-science-for-beginners

10 Weeks, 20 Lessons, Data Science for All!

deep-learning-with-python-notebooks

Jupyter notebooks for the code samples of the book "Deep Learning with Python"

football_analytics

📊⚽ A collection of football analytics projects, data, and analysis by Edd Webster (@eddwebster), including a curated list of publicly available resources published by the football analytics community.

learning-opencv-4-computer-vision-with-python-third-edition

Learning OpenCV 4 Computer Vision with Python 3 – Third Edition, published by Packt

llms-from-scratch

Implementing a ChatGPT-like LLM from scratch, step by step

machine-learning

深度学习与图像识别：原理与实践

machine-learning-engineering-with-python-second-edition

machine-learning-in-biotechnology-and-life-sciences

Machine Learning in Biotechnology using Python, published by Packt

memae-anomaly-detection

MemAE for anomaly detection. -- Gong, Dong, et al. "Memorizing Normality to Detect Anomaly: Memory-augmented Deep Autoencoder for Unsupervised Anomaly Detection". ICCV 2019.

mldd24

The repository for the course "Machine Learning in Drug Design" taught at the Jagiellonian University in 2024. The page is hosted by the machine learning research group GMUM.

practice

python-business-analytics

Python solutions to solve practical business problems.

scrna-seq_notes

A list of scRNA-seq analysis tools

segment-everything-everywhere-all-at-once

[NeurIPS 2023] Official implementation of the paper "Segment Everything Everywhere All at Once"

single-cell-best-practices

https://www.sc-best-practices.org

springboard-datasciencetrack-student

Springboard Program: Data Science Career Track - NLP

themlsbook

This repository is a supplement to the 'Machine Learning Simplified: A Gentle Introduction to Supervised Learning' book.

torchmd

End-To-End Molecular Dynamics (MD) Engine using PyTorch

torchmd-net

Neural network potentials based on graph neural networks and equivariant transformers

torchmd-protein-thermodynamics

Tutorials and data necessary to reproduce the results of publication Machine Learning Coarse-Grained Potentials of Protein Thermodynamics