Search Results for "optimizer windows" - Page 2
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Showing 126 open source projects for "optimizer windows"
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MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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EAGO.jl
A development environment for robust and global optimization
EAGO is an open-source development environment for robust and global optimization in Julia. EAGO is a deterministic global optimizer designed to address a wide variety of optimization problems, emphasizing nonlinear programs (NLPs), by propagating McCormick relaxations along the factorable structure of each expression in the NLP. Most operators supported by modern automatic differentiation (AD) packages (e.g., +, sin, cosh) are supported by EAGO and a number of utilities for sanitizing... -
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SkillOpt
Text-space optimizer that trains reusable natural-language skills
SkillOpt is a Microsoft research project for improving frozen LLM agents by optimizing reusable natural-language skill documents. Instead of changing model weights, it treats a compact skill file as the trainable state of the agent. The system learns from agent rollouts, reflection, bounded edits, and validation gates to produce better instructions over time. Its output is a deployable best_skill.md artifact that can be reused across agent tasks. The project is focused on making agents more... -
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LLM From Scratch
Build and train a GPT-style language model
LLM From Scratch is a hands-on educational workshop project that teaches developers how to build and train a GPT-style language model entirely from scratch using PyTorch. Instead of relying on high-level abstractions or prebuilt frameworks, the project walks users through implementing every core component manually, including tokenization, transformer architecture, training loops, and autoregressive text generation. The repository is intentionally simplified to focus on conceptual clarity,... -
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neural-style in TensorFlow
Neural style in TensorFlow
neural-style in TensorFlow is a TensorFlow implementation of neural style transfer. It creates a new image by combining the content of one image with the artistic style of one or more style images. The project uses TensorFlow automatic differentiation and the Adam optimizer rather than the original L-BFGS approach. Users can run it from the command line by providing a content image, style image inputs, and an output path. It supports checkpoint outputs, iteration control, style blending, and... -
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PyTorch Forecasting
Time series forecasting with PyTorch
PyTorch Forecasting aims to ease state-of-the-art time series forecasting with neural networks for both real-world cases and research alike. The goal is to provide a high-level API with maximum flexibility for professionals and reasonable defaults for beginners. A time series dataset class that abstracts handling variable transformations, missing values, randomized subsampling, multiple history lengths, etc. A base model class that provides basic training of time series models along with... -
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Binaryen
Compiler infrastructure and toolchain library for WebAssembly
Binaryen is a compiler and toolchain infrastructure library for WebAssembly, written in C++. It aims to make compiling to WebAssembly easy, fast, and effective. Binaryen has a simple C API in a single header, and can also be used from JavaScript. It accepts input in WebAssembly-like form but also accepts a general control flow graph for compilers that prefer that. Binaryen's internal IR uses compact data structures and is designed for completely parallel codegen and optimization, using all... -
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autoresearch
AI agents autonomously run and improve ML experiments overnight
autoresearch is an experimental framework that enables AI agents to autonomously conduct machine learning research by iteratively modifying and training models. Created by Andrej Karpathy, the project allows an agent to edit the model training code, run short experiments, evaluate results, and repeat the process without human intervention. Each experiment runs for a fixed five-minute training window, enabling rapid iteration and consistent comparison across architectural or hyperparameter... -
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StructuralEquationModels.jl
A fast and flexible Structural Equation Modelling Framework
This is a package for Structural Equation Modeling in development. It is written for extensibility, that is, you can easily define your own objective functions and other parts of the model. At the same time, it is (very) fast. We provide fast objective functions, gradients, and for some cases hessians as well as approximations thereof. As a user, you can easily define custom loss functions. For those, you can decide to provide analytical gradients or use finite difference approximation /... -
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Robyn
Experimental, AI/ML-powered and open sourced Marketing Mix Modeling
Robyn is an open-source, AI/ML-powered Marketing Mix Modeling (MMM) toolkit developed by Meta Marketing Science under the “facebookexperimental” GitHub umbrella. Its goal is to democratize rigorous MMM: what traditionally required expert statisticians and expensive consulting becomes accessible to any company with data. Robyn takes in historical data (spends on different marketing channels, conversions, or revenue, and optional context or organic-media variables) and uses a combination of... -
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UglifyJS 3
JavaScript parser, mangler, compressor, beautifier toolkit
UglifyJS is a JavaScript compressor/minifier written in JavaScript. It also contains tools that allow one to automate working with JavaScript code. A parser which produces an abstract syntax tree (AST) from JavaScript code. A code generator which outputs JavaScript code from an AST, also providing the option to get a source map. A compressor (optimizer). it uses the transformer API to optimize an AST into a smaller one. A mangler, reduce names of local variables to (usually) single-letters.... -
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OptiPNG
Advanced PNG optimization program
OptiPNG is a PNG optimizer that recompresses image files to a smaller size, without losing any information. This program also converts external formats (BMP, GIF, PNM and TIFF) to optimized PNG, and performs PNG integrity checks and corrections. -
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CCleaner
Clean up, speed up, and optimize your PC
CCleaner is a trusted PC optimization tool for Windows or Mac designed to clean, speed up, and secure your computer. It removes junk files, temporary data, and broken settings that slow down system performance over time. The software includes powerful modules like Performance Optimizer, Driver Updater, and Cloud Drive Cleaner, helping you reclaim storage space and improve efficiency. -
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JSoko
The Sokoban game implemented in Java.
JSoko is a Java program for playing the Sokoban game. It features path finding, auto push, auto solving, undo/redo, deadlock detection, and more. -
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comfymodeldownloader
Automate ComfyUI model downloads via URL or name into correct folders
Short Description Tired of red error nodes? The ComfyUI Model Downloader automatically analyzes your workflows via AI, tracks down missing models, and manages your heavy files with an integrated Archive Manager. The ultimate SSD-saver and a must-have standalone Java tool for every ComfyUI power user! We’ve all been there... You find an amazing workflow, drag it into ComfyUI, and... RED. Error messages everywhere because you're missing specific models. You spend the next 20 minutes... -
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Bytecoder
Framework to interpret and transpile JVM bytecode to JavaScript
Bytecoder is a Rich Domain Model for Java Bytecode and Framework to interpret and transpile it to other languages such as JavaScript, OpenCL or WebAssembly. The JVM Bytecode is parsed and transformed into an intermediate representation. This intermediate representation is passed thru optimizer stages and sent to a backend implementation for target code generation. The JavaScript backend transforms the intermediate representation into JavaScript. -
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Greenplum Database
Massive parallel data platform for analytics, machine learning and AI
Rapidly create and deploy models for complex applications in cybersecurity, predictive maintenance, risk management, fraud detection, and many other areas. With its unique cost-based query optimizer designed for large-scale data workloads, Greenplum scales interactive and batch-mode analytics to large datasets in the petabytes without degrading query performance and throughput. Based on PostgreSQL, Greenplum provides you with more control over the software you deploy, reducing vendor... -
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SSD in PyTorch 1.0
High quality, fast, modular reference implementation of SSD in PyTorch
This repository implements SSD (Single Shot MultiBox Detector). The implementation is heavily influenced by the projects ssd.pytorch, pytorch-ssd and maskrcnn-benchmark. This repository aims to be the code base for research based on SSD. Multi-GPU training and inference: We use DistributedDataParallel, you can train or test with arbitrary GPU(s), the training schema will change accordingly. Add your own modules without pain. We abstract backbone, Detector, BoxHead, BoxPredictor, etc. You can... -
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tyrant_optimize
TUO
Tyrant Unleashed Optimizer (the SIM) -
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FairScale
PyTorch extensions for high performance and large scale training
FairScale is a collection of PyTorch performance and scaling primitives that pioneered many of the ideas now used for large-model training. It introduced Fully Sharded Data Parallel (FSDP) style techniques that shard model parameters, gradients, and optimizer states across ranks to fit bigger models into the same memory budget. The library also provides pipeline parallelism, activation checkpointing, mixed precision, optimizer state sharding (OSS), and auto-wrapping policies that reduce... -
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V8 Perf
Notes and resources related to v8 and thus Node.js performance
V8 Perf is an educational collection of notes and resources about V8 internals and JavaScript performance in Node.js. It explains how V8 represents JavaScript data internally and how those representations can influence execution speed. Compiler documentation explores the Ignition interpreter, TurboFan optimizer, optimization decisions, and deoptimization behavior. Memory sections explain heap organization, garbage collection, object references, allocations, and leak investigation. Profiling... -
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Elephas
Distributed Deep learning with Keras & Spark
Elephas is an extension of Keras, which allows you to run distributed deep learning models at scale with Spark. Elephas currently supports a number of applications. Elephas brings deep learning with Keras to Spark. Elephas intends to keep the simplicity and high usability of Keras, thereby allowing for fast prototyping of distributed models, which can be run on massive data sets. Elephas implements a class of data-parallel algorithms on top of Keras, using Spark's RDDs and data frames. Keras... -
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CSSO
CSS minifier with structural optimizations
CSSO (CSS Optimizer) is a CSS minifier. It performs three sorts of transformations: cleaning (removing redundant), compression (replacement for the shorter forms), and restructuring (merge of declarations, rules, and so on). As a result, an output CSS becomes much smaller in size. One of CDN services like unpkg or jsDelivr can be used. By default (for short path) the ESM version is exposed. For IIFE version a full path to a bundle should be specified. CSSO is based on CSSTree to parse CSS... -
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YOLOV3 Pytorch
This is a source code for yolo3-pytorch
YOLOV3 Pytorch is a PyTorch implementation of the YOLOv3 object detection model built for training, prediction, and evaluation. The repository provides a complete workflow for users who want to train their own object detector with VOC-style data or use pretrained weights. It includes utilities for annotation conversion, anchor generation, image prediction, video prediction, batch prediction, FPS measurement, heatmap output, and mAP evaluation. The project added multi-GPU training, target... -
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YOLOV4 Pytorch
This is a source code for YoloV4-pytorch that can be used to train you
YOLOV4 Pytorch is a PyTorch implementation of the YOLOv4 object detection model for training and running custom detection systems. The repository is structured around practical workflows, including training, prediction, evaluation, anchor generation, model configuration, and dataset annotation utilities. It supports VOC-style datasets and includes scripts for prediction, mAP evaluation, FPS testing, video prediction, batch prediction, and heatmap generation. The project added multi-GPU...
