Neural Network Open Source Projects
Discover 3 open source Neural Network repositories from GitHub, each with an analysis of what it does, key features, use cases and alternatives. Neural Network projects here are most often combined with Machine Learning, Python and Artificial Intelligence. Last updated July 21, 2026.
AsterMind-ELM: Modular Extreme Learning Machine for On-Device ML in JS/TS
AsterMind-ELM is a JavaScript/TypeScript library that modernizes Extreme Learning Machines (ELMs) for instant, on-device machine learning in web applications. It offers advanced features like Kernel ELMs, Online ELM, and DeepELM, enabling fast, private, and interpretable AI directly in the browser. This framework allows for building decentralized, self-training ML systems without relying on GPUs or servers.
NVIDIA NeMo Speech: Scalable Generative AI for Speech Models
NVIDIA NeMo Speech is a powerful, scalable generative AI framework designed for researchers and developers focused on Large Language Models, Multimodal, and Speech AI. It provides tools for Automatic Speech Recognition (ASR) and Text-to-Speech (TTS), enabling efficient creation, customization, and deployment of new AI models using existing code and pre-trained checkpoints. This framework supports a wide range of applications, from real-time streaming ASR to high-quality multilingual TTS.
AIMET: Advanced Quantization and Compression for Neural Networks
AIMET, the AI Model Efficiency Toolkit, is an open-source Python library developed by Qualcomm Innovation Center, Inc. It provides advanced techniques for quantizing and compressing trained deep learning models. This toolkit helps improve runtime performance and reduce memory footprint, making models more efficient for deployment on edge devices while minimizing accuracy loss.