Implementation of basic machine learning algorithms.
-
Updated
Sep 27, 2018 - Python
Implementation of basic machine learning algorithms.
Text , Human Pose , Vehicle detector using pre trained models of openvino toolkit
Inferfuzzy es un biblioteca de Python para implementar Sistemas de Inferencia Difusa
DaisyKit examples for Android
Three real-world scenarios given to analyze and optimize their queuing systems. This project demonstrates how to identify the appropriate Intel Hardware types that will work best for the manufacturing, and retail, and transportation scenarios. This application uses Intel DevCloud.
Mokka is a minimal Inference Engine for Dense Layer Neural Networks. Written on a single C# header, it uses AVX2
trying to write a mini triton backend in rust
Filling in the missing gaps with langchain, and creating OO wrappers to simplify some workloads.
high-performance description logic reasoner
Fuzzy Sharper is a C# that allows you to create your own Fuzzy Expert System
Fully asynchronous telegram bot for age and gender recognition based on aiogram and OpenVINO™
Programa en Python para manejar y crear imagenes con Stable Diffusion Corriendo En GPU AMD.
an Expert System in Egyption divorce law
What Happen Next ? Live Inference
MIVisionX Python Inference Application using pre-trained ONNX/NNEF/Caffe models
Project #2 for Intel's Udacity Nanodegree Program, using Intel's OpenDev Cloud for benchmarking different use case scenarios for deploying OpenVino on edge devices
(WIP) 🚀 High performance nerual network inference engine running on Web.
Pure Java Llama2 inference with optional multi-GPU CUDA implementation
Add a description, image, and links to the inference-engine topic page so that developers can more easily learn about it.
To associate your repository with the inference-engine topic, visit your repo's landing page and select "manage topics."