Search Results for "machine learning platform" - Page 6
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Showing 571 open source projects for "machine learning platform"
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Tile Kernels
A kernel library written in tilelang
Tile Kernels is a DeepSeek kernel library written with TileLang for high-performance AI and machine-learning workloads. It contains specialized kernels for areas such as mixture-of-experts routing, quantization, batched transpose operations, Engram gating, and Manifold HyperConnection components. The project includes both optimized kernel implementations and PyTorch reference versions for comparison and validation. It is aimed at developers and researchers who work close to model internals and need efficient low-level building blocks. ... -
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FairChem
FAIR Chemistry's library of machine learning methods for chemistry
FAIRChem is a unified library for machine learning in chemistry and materials, consolidating data, pretrained models, demos, and application code into a single, versioned toolkit. Version 2 modernizes the stack with a cleaner core package and breaking changes relative to V1, focusing on simpler installs and a stable API surface for production and research. The centerpiece models (e.g., UMA variants) plug directly into the ASE ecosystem via a FAIRChem calculator, so users can run relaxations, molecular dynamics, spin-state energetics, and surface catalysis workflows with the same pretrained network by switching a task flag. ... -
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Imagen - Pytorch
Implementation of Imagen, Google's Text-to-Image Neural Network
Implementation of Imagen, Google's Text-to-Image Neural Network that beats DALL-E2, in Pytorch. It is the new SOTA for text-to-image synthesis. Architecturally, it is actually much simpler than DALL-E2. It consists of a cascading DDPM conditioned on text embeddings from a large pre-trained T5 model (attention network). It also contains dynamic clipping for improved classifier-free guidance, noise level conditioning, and a memory-efficient unit design. It appears neither CLIP nor prior... -
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Kornia
Open Source Differentiable Computer Vision Library
Kornia is a differentiable computer vision library for PyTorch. It consists of a set of routines and differentiable modules to solve generic computer vision problems. At its core, the package uses PyTorch as its main backend both for efficiency and to take advantage of the reverse-mode auto-differentiation to define and compute the gradient of complex functions. Inspired by existing packages, this library is composed by a subset of packages containing operators that can be inserted within... -
Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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Claude Code Projects Index
An index of my Claude Code related repos
...It is particularly valuable for developers exploring the Claude ecosystem and looking for inspiration or best practices. The repository is continuously updated, reflecting the evolving landscape of AI-assisted development. It also serves as a knowledge-sharing platform, highlighting innovative approaches and implementations. Overall, it acts as a discovery hub that accelerates learning and adoption of AI development tools. -
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FlutterUnit
All Platform Flutter Experience App
FlutterUnit is a Flutter-based educational app for measuring various physical units and conversions. It includes calculators for multiple unit categories (length, mass, volume, etc.), conversion tools, and UI components demonstrating modular architecture and state management patterns. Ideal for learning Flutter UI & business logic structure. -
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tslab
Interactive JavaScript and TypeScript programming with Jupyter
tslab is an interactive programming environment and REPL with Jupyter for JavaScript and TypeScript users. You can write and execute JavaScript and TypeScript interactively on browsers and save results as Jupyter notebooks. -
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Nerves
Craft and deploy bulletproof embedded software in Elixir
Nerves is the open-source platform and infrastructure you need to build, deploy, and securely manage your fleet of IoT devices at speed and scale. Nerves is written in Elixir, but you don’t have to rewrite everything in Elixir to get the advantages of Nerves, simply bring your own code (like C, C++, Python, Rust, and more) and scale up. Nerves use the Erlang runtime system, known for being distributed, fault-tolerant, soft real-time, and highly available. Nerves has the tools you need to... -
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Spring Statemachine
Framework for application developers to use state machine concepts
.../gradlew is invoked from the root of the source tree and serves as a cross-platform, self-contained bootstrap mechanism for the build. -
Stop Cyber Threats with VM-Series Next-Gen Firewall on AzureGain integrated visibility across all traffic in a single pass. Deploy Palo Alto Networks VM-Series to determine application identity and content while automating security policy updates via rich APIs.
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NVIDIA Warp
A Python framework for accelerated simulation, data generation
...It enables developers to write kernel-level code in Python that is automatically compiled into efficient CUDA kernels, combining ease of use with near-native performance. The framework is designed for applications such as robotics, reinforcement learning, physical simulation, and differentiable computing, where performance and flexibility are critical. Warp provides a set of primitives for working with arrays, geometry, and physics operations, allowing users to implement complex simulations without writing low-level CUDA code directly. It also supports differentiable programming, enabling gradients to be computed through simulation pipelines, which is particularly valuable for machine learning integration. -
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PRML
PRML algorithms implemented in Python
PRML repository is a respected and well-maintained project that implements the foundational algorithms from the famous textbook Pattern Recognition and Machine Learning by Christopher M. Bishop, providing a practical and accessible Python reference for both students and professionals. Rather than just summarizing concepts, the repository includes working code that demonstrates linear regression and classification, kernel methods, neural networks, graphical models, mixture models with EM algorithms, approximate inference, and sequential data methods — all following the book’s structure and notation. ... -
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Zeebe
Distributed Workflow Engine for Microservices Orchestration
Automate processes at scale with unprecedented performance and resilience. Zeebe is the workflow and decision engine that powers Camunda Platform 8. Zeebe’s cloud-native design provides the performance, resilience, and security enterprises need to future-proof their process orchestration efforts. Zeebe distributes data across all brokers in a cluster with storage directly on the server filesystem. If one broker goes down, another can replace it with no data loss. This pre-configured replication mechanism ensures that Camunda Platform 8 can recover from machine or software failure with no human interaction, no data loss and minimal downtime. -
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Lean 4
Lean 4 programming language and theorem prover
Lean 4 is both a programming language and an interactive theorem prover, designed to support formal reasoning while also functioning as an efficient and extensible general-purpose language. The project serves researchers, mathematicians, programmers, and formal methods users who need a system for writing machine-checked proofs as well as executable programs in the same environment. One of its defining characteristics is its emphasis on extensibility, since Lean 4 is built to allow users to develop custom automation, metaprogramming tools, and domain-specific extensions instead of being limited to a fixed proving workflow. The broader Lean ecosystem also includes official tutorials, language references, examples, and installation and build tools, which reflects that the project is not just a core compiler repository but the center of a mature development platform. -
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Celest
The Flutter cloud platform
...To get started with Celest, you'll need to configure your development environment so that you have Flutter and the Celest CLI installed on your machine. -
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Go Cursor Help
Cursor Free Trial Reset Tool
A small CLI utility written in Go to reset free trial restrictions of the Cursor AI code assistant on local machines. It automates machine‑ID resets and environment cleanups so users can bypass "Too many free trial accounts" limitations across platforms. -
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MIVisionX
Set of comprehensive computer vision & machine intelligence libraries
MIVisionX toolkit is a set of comprehensive computer vision and machine intelligence libraries, utilities, and applications bundled into a single toolkit. AMD MIVisionX delivers highly optimized open-source implementation of the Khronos OpenVX™ and OpenVX™ Extensions along with Convolution Neural Net Model Compiler & Optimizer supporting ONNX, and Khronos NNEF™ exchange formats. The toolkit allows for rapid prototyping and deployment of optimized computer vision and machine learning inference workloads on a wide range of computer hardware, including small embedded x86 CPUs, APUs, discrete GPUs, and heterogeneous servers. ... -
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NetPad
A cross-platform C# editor and playground
...Query databases using LINQ or SQL effortlessly. Experiment with new C# features or start learning C# in an intuitive and accessible environment. Create and save your own utility or administration scripts for repeated use. -
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ModelingToolkit.jl
Modeling framework for automatically parallelized scientific ML
ModelingToolkit.jl is a modeling language for high-performance symbolic-numeric computation in scientific computing and scientific machine learning. It then mixes ideas from symbolic computational algebra systems with causal and acausal equation-based modeling frameworks to give an extendable and parallel modeling system. It allows for users to give a high-level description of a model for symbolic preprocessing to analyze and enhance the model. Automatic symbolic transformations, such as index reduction of differential-algebraic equations, make it possible to solve equations that are impossible to solve with a purely numeric-based technique. ... -
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LoopVectorization.jl
Macro(s) for vectorizing loops
...It analyzes loops and generates highly efficient code that leverages CPU vector instructions, making it ideal for performance-critical computing in fields such as scientific computing, signal processing, and machine learning. -
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Otter-Grader
A Python and R autograding solution
...It is designed to work with classes at any scale by abstracting away the autograding internals in a way that is compatible with any instructor's assignment distribution and collection pipeline. Otter supports local grading through parallel Docker containers, grading using the autograder platforms of 3rd party learning management systems (LMSs), the deployment of an Otter-managed grading virtual machine, and a client package that allows students to run public checks on their own machines. Otter is designed to grade Python scripts and Jupyter Notebooks, and is compatible with a few different LMSs, including Canvas and Gradescope. -
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Codon
A high-performance, zero-overhead, extensible Python compiler
Codon is a high-performance Python compiler that compiles Python code to native machine code without any runtime overhead. Typical speedups over Python are on the order of 100x or more, on a single thread. Codon supports native multithreading which can lead to speedups many times higher still. The Codon framework is fully modular and extensible, allowing for the seamless integration of new modules, compiler optimizations, domain-specific languages and so on. We actively develop Codon... -
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nbmake
Pytest plugin for testing notebooks
Pytest plugin for testing and releasing notebook documentation. To raise the quality of scientific material through better automation. Research/Machine Learning Software Engineers who maintain packages/teaching materials with documentation written in notebooks. -
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The Algorithms Python
All Algorithms implemented in Python
...Each implementation is designed with clarity in mind, favoring readability and comprehension over performance optimization. The project covers various domains including mathematics, cryptography, machine learning, sorting, graph theory, and more. With contributions from a large global community, it continually grows and improves through collaboration and peer review. This repository is an ideal reference for students, educators, and developers seeking hands-on experience with algorithmic concepts in Python. -
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Deployer
Deployment tool with support for popular frameworks out of the box
A deployment tool written in PHP with support for popular frameworks out of the box. Deployer is a cli tool for deployment of any PHP applications, including frameworks such as Laravel, Symfony, Zend Framework and many more. Main concept of Deployer is recipe, a php file containing tasks definitions. Recipe can require other recipes and extend/ override functionality. Also Deployer comes with bunch of ready to use recipes from community for Slack, etc. Deployer can be easily installed via... -
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ohmyposh.dev
A prompt theme engine for any shell
...From standard segments all the way to custom implementations. No matter which shell you're using, or even how many, you can carry the configuration from one shell and/or machine to another for the same prompt everywhere you work. What started as the offspring of oh-my-posh2 for PowerShell resulted in a cross platform, highly customizable and extensible prompt theme engine. After 4 years of working on oh-my-posh, a modern and more efficient tool was needed to suit my personal needs. When you look at prompts like Agnoster or Paradox, you notice they usually consist of a few building blocks which contain one or more segments that display some sort of information. ...