An open-access book on numpy vectorization techniques, Nicolas P. Rougier, 2017

VMAS is a vectorized differentiable simulator designed for efficient Multi-Agent Reinforcement Learning benchmarking. It is comprised of a vectorized 2D physics engine written in PyTorch and a set of challenging multi-robot scenarios. Additional scenarios can be implemented through a simple and modular interface.

A web UI Project In order to learn the large language model. This project includes features such as chat, quantization, fine-tuning, prompt engineering templates, and multimodality.

[SIGGRAPH 2021] General Virtual Sketching Framework for Vector Line Art

Bitmap to Vector Conversion. Woodcut, guilloche, halftone effects

A vectorized implementation of py_vollib, that supports numpy arrays and pandas Series and DataFrames.

An application to translate raster image of CAD drawing sheet to a user editable DXF format.

fast + parallel AlphaZero in JAX

Multi-threaded matrix multiplication and cosine similarity calculations for dense and sparse matrices. Appropriate for calculating the K most similar items for a large number of items by chunking the item matrix representation (embeddings) and using Numba to accelerate the calculations.

Vectorization techniques for fast population-based training.

Implementation of Motion Planning via Optimal Transport (MPOT) in PyTorch, NeurIPS 2023.

QGIS plugin to digitize lines and polygons from raster maps using AI

Extension to hypothesis for testing numpy general universal functions

alternative illustration2vec implitation of sigmoids of fully connected layer

Load embeddings and featurize your sentences.

Computing FLOPs with Intel Software Development Emulator (Intel SDE)

A simple vectorized implementation of a Convolutional Neural Network in plain Numpy && more

Interactive chat application leveraging OpenAI's GPT-4 for real-time conversation simulations. Built with Flask, this project showcases streaming LLM responses in a user-friendly web interface.

Fake News Detection - Feature Extraction using Vectorization such as Count Vectorizer, TFIDF Vectorizer, Hash Vectorizer,. Then used an Ensemble model to classify whether the news is fake or not.

Convert raster-to-vector floorplan vectors to Plan2Scene input formats.