An Open Source Machine Learning Framework for Everyone

PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice （『飞桨』核心框架，深度学习&机器学习高性能单机、分布式训练和跨平台部署）

Machine learning library, Distributed training, Deep learning, Models

Tensors and Dynamic neural networks in Python with strong GPU acceleration

Crypto & Stock* price prediction with regression models.

A parallel hybrid neural network (PHNN) model for price forecasting. Codes for paper “Energy price prediction based on decomposed price dynamics: A parallel neural network approach”, Applied Soft Computing (2024), doi: https://doi.org/10.1016/j.asoc.2024.111972.

High-level library to help with training and evaluating neural networks in PyTorch flexibly and transparently.

This is my source code during my research intern at Indian Institute of Information Technology (IIIT), Guwahati

Support project for my Bachelor's thesis @ Unifi - Converting Oxford5k and Paris6k into datasets suitable for object detection tasks. This repository contains scripts to create XML (PASCAL VOC format) and JSON (COCO format) annotations from .pkl files, enabling the training of an SSD/MobileNet object detection model.

🦋 A personal research and development (R&D) lab that facilitates the sharing of knowledge.

GoogleNet Architecture is trained on CIFAR10 Dataset and LSTM Architecture is trained on IBM Stocks Dataset

Qdrant - High-performance, massive-scale Vector Database for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/

Deep Learning Neural Network Architectures - LeNet and AlexNet, both trained on CIFAR10 and CIFAR100 Datasets

This code trains a chatbot utilizing technologies such as Pandas and Pickle to load, preprocess, and vectorize datasets, ensuring they are ready for model training and evaluation, uses keras and Tokenizer to design and implement a deep learning model using LSTM

A GPU-accelerated library containing highly optimized building blocks and an execution engine for data processing to accelerate deep learning training and inference applications.

Semi-Supervise cellular deconvolution of Bulk RnaSeq using NMF and CiberSortx, DCQ or others

High-efficiency floating-point neural network inference operators for mobile, server, and Web

This repository contains a project utilizing Wavenet technology to solve family seating arrangement problems. The aim is to optimize seating arrangements to meet specified criteria, ensuring a pleasant and organized experience for family gatherings.

Matnn (Music Audio Tagger Neural Net) is a rest compliant music tag service utilizing a batch queuing system (Kueue) running on a Kubernetes cluster. Matnn utilizes the (Discogs-EffNet) model from (Essentia) to predict music classification, BPM (Beats per minute) and tonal/key scale from over 400 genres of music.

Open-source Platform for Engineering Neural Architectures and Research Collaboration. Developing and improving AI tools for everyone.