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master-machine-learning-algorithms

This is a repository for notes and codes of reading the book --- Jason Brownlee Master Machine Learning Algorithms

math-edu

Educational materials on deep learning by Weights & Biases

mesa-abm-tutorial

mesa-examples

Seminal agent-based models developed using Mesa

mit-deep-learning

Tutorials, assignments, and competitions for MIT Deep Learning related courses.

ml_ebooks

These are Some useful ebook

ml_model_for_predicting_ships_crew_size

models-from-scratch-python

Repo where I recreate some popular machine learning models from scratch in Python

neural-networks

neural-networks-and-deep-learning

Code samples for my book "Neural Networks and Deep Learning"

ng-video-lecture

open-source-research-notebooks

Jupyter notebooks helping open source researchers, journalists, and fact-checkers use command line tools and code projects for digital investigations.

organization-visualization-python

phi-3cookbook

This is a Phi-3 book for getting started with Phi-3. Phi-3, a family of open AI models developed by Microsoft. Phi-3 models are the most capable and cost-effective small language models (SLMs) available, outperforming models of the same size and next size up across a variety of language, reasoning, coding, and math benchmarks.

predicting_fetal_diseases_with_ml

project-mesa-presentations

Mesa presentations

pykan

Kolmogorov Arnold Networks

python-cheatsheet

stanford-cs-229-machine-learning

VIP cheatsheets for Stanford's CS 229 Machine Learning

streamlit-for-data-science

A repo for the book 'Streamlit for Data Science' by Tyler Richards

swe-agent

SWE-agent takes a GitHub issue and tries to automatically fix it, using GPT-4, or your LM of choice. It solves 12.47% of bugs in the SWE-bench evaluation set and takes just 1 minute to run.

t81_558_deep_learning

T81-558: Keras - Applications of Deep Neural Networks @Washington University in St. Louis

think-complexity2

Book and code for Think Complexity, 2nd edition

tinyml-papers-and-projects

This is a list of interesting papers and projects about TinyML.

unsupervised_ml_from_scratch

This repository is dedicated for those who would like to get a hands-on experiense in Unsupervised Machine Learning algorythms. The idea is to write the algorythms from scratch based on the intrinsic understanding of the algorythm, i.e., with the minimum necessary extra packages. I will describe the algorythm and upload my Python codes. The comment