kawdoco

distributed_multi_model_biometric_system

Machine Learning biometric authentication Distributed and large data

DynaAgent

MULTI-AGENT BASED DYNAMIC SCHEDULING SYSTEM FOR MANUFACTURING

gpt4all

gpt4all: a chatbot trained on a massive collection of clean assistant data including code, stories and dialogue

langchain-tutorials

Overview and tutorial of the LangChain Library

spaCy

💫 Industrial-strength Natural Language Processing (NLP) in Python

langchain

⚡ Building applications with LLMs through composability ⚡

artificial-intelligence

AI projects in python, mostly Jupyter notebooks.

Auto-PyTorch

Automatic architecture search and hyperparameter optimization for PyTorch

auto-sklearn

Automated Machine Learning with scikit-learn

ChatBot-Conference-2022

chatgpt-retrieval-plugin

CocosCreator_Admob_Sample

How to configure Admob for Cocos Creator mobile application

downward

The Fast Downward domain-independent classical planning system

kawdoco

laravel-sendgrid-driver

This library can add sendgrid driver into the laravel's mail configure.

ML-Papers-Explained

Explanation to key concepts in ML

mlbookcamp-code

The code from the Machine Learning Bookcamp book and a free course based on the book

MLJ.jl

A Julia machine learning framework

polars

Fast multi-threaded, hybrid-out-of-core DataFrame library in Rust | Python | Node.js

RockyML

⛰️ RockyML - A High-Performance Scientific Computing Framework for Non-smooth Machine Learning Problems

segment-anything-video

MetaSeg: Packaged version of the Segment Anything repository

small-text

Active Learning for Text Classification in Python

sparrow

Data extraction from documents with ML

stw-mappings

Mappings for STW Thesaurus for Economics

TinyLiDAR_NET_SNN

UdemyPythonInt

Vectorflow

A simple light-weight neural network library developed using only Numpy vectors.

whisper-jax

xturing

Build and control your own LLMs

ZTM-DS-and-Algo-Python

Contains all the code samples from the Zero to Mastery : Master the Coding Interview - Data Structures + Algorithms course by Andrei Neagoie, in Python.