Repository Index

Instant Kubernetes-Native Application Observability

• golang
• kubernetes
• ebpf
• vega

General purpose GPU compute framework built on Vulkan to support 1000s of cross vendor graphics cards (AMD, Qualcomm, NVIDIA & friends). Blazing fast, mobile-enabled, asynchronous and optimized for advanced GPU data processing usecases. Backed by the Linux Foundation.

• vulkan
• vulkan-compute
• vulkan-example
• vulkan-tutorial

C++ image processing and machine learning library with using of SIMD: SSE, AVX, AVX-512, AMX for x86/x64, NEON, SVE for ARM, HVX for Hexagon

• simd
• avx
• neon
• image-processing

:chart_with_upwards_trend: Adaptive: parallel active learning of mathematical functions

• adaptive-learning
• machine-learning
• python
• live-plots

GRASS - free and open-source geospatial processing engine

• grass-gis
• geospatial
• geospatial-analysis
• raster

:four_leaf_clover: Evolutionary optimization library for Go (genetic algorithm, partical swarm optimization, differential evolution)

• go
• optimization
• parallel
• machine-learning

The world's cleanest AutoML library ✨ - Do hyperparameter tuning with the right pipeline abstractions to write clean deep learning production pipelines. Let your pipeline steps have hyperparameter spaces. Design steps in your pipeline like components. Compatible with Scikit-Learn, TensorFlow, and most other libraries, frameworks and MLOps environments.

• pipeline
• pipeline-framework
• machine-learning
• deep-learning

AI Vim/Neovim code generation plugin (OpenAI, ChatGPT, and more)

• code-generation
• neovim
• openai
• gpt-3

An OCaml kernel for Jupyter (IPython) notebook

• ocaml
• functional-programming
• jupyter-kernels
• machine-learning

Accelerated tensor operations and dynamic neural networks based on reverse mode automatic differentiation for every device that can run Swift - from watchOS to Linux

• deep-learning
• deep-neural-networks
• gradient-descent
• automatic-differentiation

Support vector machines (SVMs) and related kernel-based learning algorithms are a well-known class of machine learning algorithms, for non-parametric classification and regression. liquidSVM is an implementation of SVMs whose key features are: fully integrated hyper-parameter selection, extreme speed on both small and large data sets, full flexibility for experts, and inclusion of a variety of different learning scenarios: multi-class classification, ROC, and Neyman-Pearson learning, and least-squares, quantile, and expectile regression.

• svm
• regression
• classification
• machine-learning

Go's answer to pandas + scikit-learn: a batteries-included data analysis library with dataframes, statistics, machine learning, quant, and GPU acceleration. Run Python with seamless two-way variable sharing, or explore data straight from the Insyra CLI.

• parallel
• data-science
• data-visualization
• pandas

🛡️ Free AI that blocks hackers while you sleep. Runs on cheap hardware. When someone in Tokyo gets attacked, you're protected in 30 seconds. No fees. No experts needed. Just protection. One node's detection → everyone's protection.

• ai-security
• cybersecurity
• ids
• iot-security

Cryptographic Dataset Generation & Modelling Framework

• cryptography
• deep-learning
• deep-neural-networks
• machine-learning

Python3 script that transfers files in Google Colab 10-50x faster, using multi-threaded parallel copying between Google Drive locations.

• colab-notebook
• multithreading
• parallel-computing
• copy