Search Results for "optimization" - Page 31
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Showing 1233 open source projects for "optimization"
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Deep Learning cheatsheets
VIP cheatsheets for Stanford's CS 230 Deep Learning
...The project organizes complex machine learning topics into visually structured reference materials that simplify studying neural networks, convolutional architectures, recurrent networks, optimization strategies, and training methodologies. It was created to help students and practitioners quickly review important formulas, workflows, and implementation concepts without navigating large textbooks or lecture archives. The repository combines concise theoretical explanations with practical training advice, making it valuable for both interview preparation and hands-on model development. ... -
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Jekyll-Paper
A simple Jekyll theme, helping you to create your own blog
Jekyll Paper is a simple Jekyll theme, and it aims to help you to create your own blog in the easiest way. Unfortunately, Jekyll Paper implements the category page by the 'Jekyll-archive' plugin, and GitHub Pages does not support it. So, this project is for the self-host blog, and the GitHub Pages version is also available in Jekyll Paper for Github. -
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nopCommerce
Free and open source ASP.NET shopping cart
nopCommerce is the most popular free & open source ASP.NET shopping cart in the world. It powers more than 60,000 live shops from SMB to Enterprise in over 100 countries. nopCommerce is a great example of an open-source product. It is transparent and open for input from developers from all over the world. The product is developed and supported by the professional team since 2008. The source code is fully customizable. Pluggable architecture makes it easy to develop custom... -
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Microarray assosiated motif analyzer
Cis-element prediction tool from microarray data
...Simulation of gene expression was performed using a support vector machine and based on the presence of predicted motifs and motif pairs. The accuracy of simulated gene expression was used to evaluate the quality of prediction and to optimize the parameters used in this method. After optimization, MAMA accurately simulated more than 87% of gene expression. See Kakei Y, Ogo Y, Itai RN, et al. (2013) Development of a novel prediction method of cis-elements to hypothesize collaborative functions of cis-element pairs in iron-deficient. Rice 6(1): 22. -
Enterprise-grade ITSM, for every businessFreshservice is an intuitive, AI-powered platform that helps IT, operations, and business teams deliver exceptional service without the usual complexity. Automate repetitive tasks, resolve issues faster, and provide seamless support across the organization. From managing incidents and assets to driving smarter decisions, Freshservice makes it easy to stay efficient and scale with confidence.
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Machine Learning cheatsheets Stanford
VIP cheatsheets for Stanford's CS 229 Machine Learning
...The project compiles concise explanations of important topics in machine learning and presents them in an accessible format that helps learners review complex ideas quickly. The repository includes summaries covering areas such as supervised learning, unsupervised learning, deep learning, and optimization techniques. In addition to machine learning algorithms, it also contains refresher materials on mathematical prerequisites including probability theory, statistics, linear algebra, and calculus. These cheat sheets are designed to serve as quick reference guides that students can use while studying or reviewing machine learning material. -
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UNMAINTAINED: Try https://github.com/pjoe/loadem instead This project aims to provide a tool for load testing web applications. The goal is a tool that is easy to use and provides near real-time performance measurements of the application under test which is very usefull during optimization.
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GeoHammerToolbox
Digital Signal Processing and Wave Field Propagation
Integration of multithread calculation and 2D/3D visualization -
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SwaNN
PSO for neural networks
SwaNN is a basic framework for neural networks based on particle swarm optimization (using the Python package PySwarms (https://pyswarms.readthedocs.io/en/latest/). The zip file contains the main programs in SwaNN.py and around 30 examples : - classification - regression - time series forecasting I need some help for class building (I am not an expert in Python nor in OOP), if somebody is interested in it... -
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DeepLearning
Deep Learning (Flower Book) mathematical derivation
...It is edited by three world-renowned experts, Ian Goodfellow, Yoshua Bengio, and Aaron Courville. Includes linear algebra, probability theory, information theory, numerical optimization, and related content in machine learning. At the same time, it also introduces deep learning techniques used by practitioners in the industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling and practical methods, and investigates topics such as natural language processing, Applications in speech recognition, computer vision, online recommender systems, bioinformatics, and video games. ... -
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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ScaffCC
Compilation and optimization framework for the Scaffold language
ScaffCC is a compiler and scheduler for the Scaffold programing language. It is written using the LLVM open-source infrastructure. It is for the purpose of writing and analyzing code for quantum computing applications. ScaffCC enables researchers to compile quantum applications written in Scaffold to a low-level quantum assembly format (QASM), apply error correction, and generate time and area metrics. It is written to be scalable up to problem sizes in which quantum algorithms outperform... -
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Fay
A proper subset of Haskell that compiles to JavaScript
Fay is a compiler for a proper subset of Haskell that type-checks using GHC and compiles to JavaScript. It supports pure functional programming, a Fay-specific monad, FFI, optional tail-call optimization, and integration with Cabal packages. GHC-compatible type checking, ensuring correctness. Lazy, pure functional semantics with a distinct Fay monad. Foreign Function Interface (FFI) to integrate native JS code. Compatible with standard Haskell packaging tools like Cabal. -
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GWOVina 1.0
The Hybrid Grey Wolf Optimization for Protein-Ligand Docking
Protein-ligand docking programs are indispensable tools for predicting the binding pose of a ligand to the receptor protein. Based on the implementation of AutoDock Vina, GWOVina employs grey wolf optimization (GWO) algorithm to speed up the search for optimal ligand poses. Our rigid docking experiments show that GWOVina has enhanced exploration capability leading to significant speedup in the search while maintaining comparable binding pose prediction accuracy to AutoDock Vina. For flexible receptor docking, GWOVina is also competitive in pose ranking. ... -
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SINGA
A distributed deep learning platform
...SINGA supports various popular optimizers including stochastic gradient descent with momentum, Adam, RMSProp, and AdaGrad, etc. SINGA records the computation graph and applies the backward propagation automatically after forward propagation. The optimization of memory are implemented in the Device class. SINGA supports loading ONNX format models and saving models defined using SINGA APIs into ONNX format, which enables AI developers to use models across different libraries and tools. SINGA supports the time profiling of each of the operators buffered in the graph. Half precision is supported to bring benefits. -
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Dosage form optimizer
Optimize dosage form based on R models (ANN, GP, FL)
Software delivers the possibility of automatic dosage form optimization based on R models. Up to now, 4 different modules are available and allow user to exploit R models created with monmlp, neuralnet, rgp, and fugeR tools. -
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Simplify
Android virtual machine and deobfuscator
Simplify virtually executes an app to understand its behavior and then tries to optimize the code so that it behaves identically but is easier for a human to understand. Each optimization type is simple and generic, so it doesn't matter what specific type of obfuscation is used. Provides a virtual machine sandbox for executing Dalvik methods. After executing a method, it returns a graph containing all possible register and class values for every execution path. It works even if some values are unknown, such as file and network I/O. ... -
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moosha-ai
An intelligent virtual assistant (IVA) or intelligent personal assista
An intelligent virtual assistant (IVA) or intelligent personal assistant (IPA) is a software agent that can perform tasks or services for an individual based on commands or questions. Sometimes the term "chatbot" is used to refer to virtual assistants generally or specifically accessed by online chat. In some cases, online chat programs are exclusively for entertainment purposes. Some virtual assistants are able to interpret human speech and respond via synthesized voices. Users can ask... -
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Weld
High-performance runtime for data analytics applications
Weld is a programming language and runtime designed to improve the performance of data-intensive applications by optimizing computations across multiple libraries. Instead of optimizing individual functions independently, Weld introduces an intermediate representation that allows different frameworks to share optimization opportunities. This approach reduces data movement between libraries and enables the system to generate highly optimized machine code for parallel execution. Weld is particularly useful for workloads involving large-scale data processing in frameworks such as NumPy, Spark, and TensorFlow. The language includes built-in constructs for expressing data-parallel operations, enabling efficient execution on modern hardware architectures. ... -
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PBTK Optimizer
Application for optimization of parameters in PBTK models
...When it is impractical to use these methods to estimate a parameter, techniques can be used to optimize parameters so that model results best fit validation data. This tool was designed to optimize a user-specified list of parameters to a user-specified PBTK model. The user also controls validation data and optimization algorithms. In addition to optimized parameters, the tool outputs statistical information about the fit of the optimized model. -
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Anime4kSharp
Anime4K implemented in C#
...The Algorithm is executed on the CPU, but utilizing all available CPU Cores. This yields to a conversion time of "only" 4432 ms when upscaling from 1080p to 2160p. This time could possibly be reduced with further optimization. Images are processed in four phases that are executed on a pixel- per- pixel basis. Each phase takes a input image and renders it to a output image. This makes it easy to port the algorithm (back) to GLSL fragment shaders. As bloc97 described in his pseudo-preprint, the Anime4K algorithm is actually quite simple. -
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DAGService
Library for storing and replicating hash-linked data over the IPFS
...Because 99% of the time, a browser or mobile (d)App only needs to be able to add and get small bits of data over the IPFS network. This library provides that, in a much smaller package (currently less than 1/2 the size of js-ipfs without much optimization -- we will continue to optimize further). It is also highly extensible, so developers need only include the features they need, keeping load times fast, and (d)Apps feeling snappy. -
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PyTracking
Visual tracking library based on PyTorch
A general python framework for visual object tracking and video object segmentation, based on PyTorch. Official implementation of the RTS (ECCV 2022), ToMP (CVPR 2022), KeepTrack (ICCV 2021), LWL (ECCV 2020), KYS (ECCV 2020), PrDiMP (CVPR 2020), DiMP (ICCV 2019), and ATOM (CVPR 2019) trackers, including complete training code and trained models. -
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anyLive
RTMP streamer, RTMP (HLS) second-on player, live streaming on demand
...The framework also includes features like GPU-based filters, screen sharing, custom rendering pipelines, and multi-stream playback, making it adaptable for complex media applications. With a focus on performance optimization and minimal resource usage, it serves as a practical reference for building production-ready streaming systems. -
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Novel Insight Scoring
Novel Insight Scoring is analytics software for scoring customers
Novel Insight Scoring is analytical CRM software for automatically scoring customers given example (scored) data. The user of the software can set optimization time and adjust risk level (pessimistic, neutral or optimistic scoring) and score new customers without detailed knowledge about data analysis and machine learning methods. The scoring results are stored in a CSV file for further processing and importing to databases etc. -
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TensorFlow Machine Learning Cookbook
Code for Tensorflow Machine Learning Cookbook
...The repository contains numerous Python scripts and Jupyter notebooks that demonstrate how to implement machine learning algorithms and neural networks using the TensorFlow framework. Each section focuses on a different aspect of machine learning development, including tensor manipulation, model training, optimization strategies, and data processing techniques. The examples illustrate how TensorFlow operations and tensors can be used to build machine learning pipelines and perform tasks such as regression, classification, and clustering. By combining theoretical explanations with executable code, the project helps developers understand how TensorFlow algorithms operate internally while also providing working examples that can be adapted for real projects. -
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GHC (Glasgow Haskell Compiler)
Mirror of the Glasgow Haskell Compiler
GHC (Glasgow Haskell Compiler) is the leading open-source compiler and interactive environment for the Haskell programming language, supporting the Haskell 2010 standard plus numerous language extensions. It compiles to native machine code (via LLVM or C), and includes the interactive GHCi REPL. For full information on building GHC, see the GHC Building Guide. Here follows a summary - if you get into trouble, the Building Guide has all the answers. For building library documentation, you'll...
