Search Results for "performance" - Page 29
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Showing 1009 open source projects for "performance"
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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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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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Render 4 Monitoring
Render Web Services for Viewing/Monitoring and Test Web Applications
Renders and aggregates other web services into static HTML monitoring output. Also implements simple and dynamic testing of web based applications using mechanize. Includes Basic authentication, and ADFS authentication for web service testing. Custom authentications can be implemented very easily with python programming. Implements PhantomJS rendering for Javascript/HTML5 dynamic web pages. Requires python3 -
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Bulk Image Optimizer and Converter
Imagine having all your images well compressed and optimized :)
Bulk Image Optimizer and Converter (Portable Executable) It allows users to choose the output format (JPEG, PNG, or WebP), set the desired image quality, and remove EXIF data. The optimized images are saved in a separate folder named "optimized" within the input folder. The tool displays progress information, including the number of images processed, the average compression ratio, and the total space saved. -
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DDoS/Dos Attack Simulator
Distributed Denial of Service Attack Simulator
...It disrupts the normal traffic of a targeted server, service, or network by overwhelming the target or its surrounding infrastructure with a flood of Internet traffic. A server that does not have protection against it can experience extremely slow performance due to all of the traffic it sends. Extensive features will be added! Mega Feature - > DoS Tool. [ 1 ] Bugs Fixes. [ 2 ] Increase in Optimization. [ 3 ] DoS Attacks. Note: The following program is intended for educational purposes only. I ( Muhammad Sami Furqan ) am not responsible for any damage you do by utilizing this software. ... -
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MAX StressTester
MAX StressTester: Python stress testing tool for max CPU, RAM and Disk
...The tool is written in Python, making it easy to use and highly customizable for stress testing purposes. The MAX StressTester tool allows users to simulate high loads of traffic on their websites or servers to test their performance and reliability under heavy usage. It can also be used to identify and diagnose performance issues, allowing developers to fine-tune their systems for optimal performance.>>> Im happy to provide source code for any other projects would want to include this into -
Custom VMs From 1 to 96 vCPUs With 99.95% UptimeLive migration and automatic failover keep workloads online through maintenance. One free e2-micro VM every month.
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FairScale
PyTorch extensions for high performance and large scale training
...FairScale puts emphasis on correctness and debuggability, offering hook points, logging, and reference examples for common trainer patterns. Although many ideas have since landed in core PyTorch, FairScale remains a valuable reference and a practical toolbox for squeezing more performance out of multi-GPU and multi-node jobs. -
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quantitative
Quantized transactions python3
The “quantitative” repository by Jack-Cherish is a tutorial-style codebase for quantitative trading written in Python — essentially a learning resource that guides users through building algorithmic trading strategies step by step. It’s organized as a sequence of lessons (lesson1, lesson2, etc.), making it approachable for learners who want to understand both theory and practice in quantitative finance. The repo is evidently tied to a popular video series (on Bilibili) that reportedly drew... -
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dein.vim
Dark powered Vim/Neovim plugin manager
dein.vim is a high-performance, feature-rich plugin manager for Vim and Neovim that enables fast startup and efficient plugin loading. It supports managing plugins from GitHub and local directories, with a design that balances speed (like vim-plug) and flexibility (like NeoBundle). Active development has ceased, with only bug fixes expected going forward. Function API and familiar patterns, without commands or dependency hell. -
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albert_zh
Implementation of A Lite Bert For Self-Supervised Learning Language
albert_zh is a Chinese ALBERT pretraining and model release repository. It implements ALBERT with TensorFlow and provides Chinese pretrained models designed to reduce parameter size while preserving strong language understanding performance. The project includes several model variants, such as tiny, small, base, large, and xlarge-style releases, giving users options for speed, size, and accuracy tradeoffs. It also provides guidance for fine-tuning downstream tasks such as sentence-pair semantic similarity and Chinese classification benchmarks. The repository includes support paths for TensorFlow, PyTorch conversion, Keras loading, TensorFlow 2.0 loading, and TensorFlow Lite deployment for mobile scenarios. ... -
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LSTMs for Human Activity Recognition
Human Activity Recognition example using TensorFlow on smartphone
LSTM-Human-Activity-Recognition is a machine learning project that demonstrates how recurrent neural networks can be used to recognize human activities from sensor data. The repository implements a deep learning model based on Long Short-Term Memory (LSTM) networks to classify physical activities using time-series data collected from wearable sensors. The project uses the well-known Human Activity Recognition dataset derived from smartphone accelerometer and gyroscope signals. Through the... -
Error to trace to log to deploy. One click. No SSH.AppSignal links every error to the trace, the trace to the log, the log to the deploy that shipped it.
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Shennina
Automating Host Exploitation with AI
Shennina is an automated host exploitation framework. The mission of the project is to fully automate the scanning, vulnerability scanning/analysis, and exploitation using Artificial Intelligence. Shennina is integrated with Metasploit and Nmap for performing the attacks, as well as being integrated with an in-house Command-and-Control Server for exfiltrating data from compromised machines automatically. Shennina scans a set of input targets for available network services, uses its AI engine... -
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aiopg
aiopg is a library for accessing a PostgreSQL database
aiopg is an asynchronous PostgreSQL database driver for Python built on top of asyncio and psycopg2. It provides support for asynchronous query execution and connection pooling, enabling efficient, non-blocking database access in Python applications. aiopg is well-suited for web services and microservices that require concurrency without threads. -
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AlphaTensor
AI discovers faster, efficient algorithms for matrix multiplication
...The repository is organized into four main components: algorithms, benchmarking, nonequivalence, and recombination. These contain implementations of the discovered matrix multiplication algorithms, tools to benchmark their real-world performance, proofs of nonequivalence among thousands of solutions, and methods for decomposing larger problems into smaller factorizations. Users can explore AlphaTensor’s discovered algorithms interactively using Colab notebooks or Python scripts. -
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ProjectQ
An open source software framework for quantum computing
ProjectQ is an open-source effort for quantum computing. It features a compilation framework capable of targeting various types of hardware, a high-performance quantum computer simulator with emulation capabilities, and various compiler plug-ins. -
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Emb-GAM
An interpretable and efficient predictor using pre-trained models
Deep learning models have achieved impressive prediction performance but often sacrifice interpretability, a critical consideration in high-stakes domains such as healthcare or policymaking. In contrast, generalized additive models (GAMs) can maintain interpretability but often suffer from poor prediction performance due to their inability to effectively capture feature interactions. In this work, we aim to bridge this gap by using pre-trained neural language models to extract embeddings for each input before learning a linear model in the embedding space. ... -
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FormaVid
Small Business Appliance
...All components are stable, open source and well supported. The appliance is built using scripts so no hidden "monkey business" and you can choose a "compatible base distro" based on your needs: familiarity; performance; security; usability; etc. Please see https://sourceforge.net/p/formavid/code/ci/master/tree/INSTALL.txt for details. The appliance is specially designed to run on the Google Cloud Platform "Free Tier" https://formavid.org/gce and has it's own custom install script https://sourceforge.net/projects/formavid/files/gcloud-gce-deployment/download with instructions https://sourceforge.net/projects/formavid/files/ provided. -
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Real-ESRGAN
Real-ESRGAN aims at developing Practical Algorithms
Real-ESRGAN is a highly popular open-source project that provides practical algorithms for general image and video restoration using deep learning-based super-resolution techniques. It extends the original Enhanced Super-Resolution Generative Adversarial Network (ESRGAN) approach by training on synthetic degradations to make results more robust on real-world images, effectively enhancing resolution, reducing noise/artifacts, and reconstructing fine detail in low-quality imagery. The... -
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Automatic YouTube subtitle generation
Using OpenAI's Whisper to automatically generate YouTube subtitles
...The tool processes media locally, extracting audio and applying speech recognition to produce accurate text outputs. It supports multiple languages and can handle different Whisper model sizes, balancing performance and accuracy. yt-whisperc is designed for automation, enabling batch processing of multiple videos for transcription workflows. It also provides options for exporting subtitles in common formats such as SRT. Overall, it simplifies the process of converting video content into searchable and accessible text. -
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BEVFormer
Implementation of BEVFormer, a camera-only framework
...Our approach achieves the new state-of-the-art 56.9\% in terms of NDS metric on the nuScenes \texttt{test} set, which is 9.0 points higher than previous best arts and on par with the performance of LiDAR-based baseline. -
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Text Classification
All kinds of text classification models and more with deep learning
...It includes classic and advanced models such as fastText, TextCNN, BERT, TextRNN, RCNN, hierarchical attention networks, seq2seq attention, Transformers, dynamic memory networks, entity networks, ensembles, and boosting methods. The repository also includes training, prediction, testing, preprocessing, sample data, cached data guidance, and performance comparison notes. Overall, it is a hands-on reference for developers and researchers who want to experiment with deep learning methods for text classification. -
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Fedhf
A Flexible Federated Learning Simulator
FedHF is a Python-based simulator for flexible, heterogeneous, and asynchronous federated learning research. It provides configurable resource models, supports asynchronous protocols, and accelerates experimentation. -
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PyTorch Transfer-Learning-Library
Transfer Learning Library for Domain Adaptation, Task Adaptation, etc.
TLlib is an open-source and well-documented library for Transfer Learning. It is based on pure PyTorch with high performance and friendly API. Our code is pythonic, and the design is consistent with torchvision. You can easily develop new algorithms or readily apply existing algorithms. We appreciate all contributions. If you are planning to contribute back bug-fixes, please do so without any further discussion. If you plan to contribute new features, utility functions or extensions, please first open an issue and discuss the feature with us. -
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ConvNeXt
Code release for ConvNeXt model
...The repository provides pretrained models, training recipes, and ablation studies demonstrating how incremental design choices collectively yield state-of-the-art performance. -
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Reskin Sensor Library
ReSkin Sensor Interfacing Library
...Machine learning allows us to learn sensor response models that are robust to variations across fabrication and time, and our self-supervised learning algorithm enables finer performance enhancement. -
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nlpaug
Data augmentation for NLP
This Python library helps you with augmenting nlp for your machine learning projects. Visit this introduction to understand Data Augmentation in NLP. Augmenter is the basic element of augmentation while Flow is a pipeline to orchestra multi augmenters together. -
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pspider
Simple Python framework for building multithreaded web crawlers
PSpider is a lightweight web crawling framework written in Python designed to simplify the development of custom web spiders. It focuses on providing an easy-to-understand architecture while still supporting concurrent crawling for improved performance. It uses a multithreaded model that separates the crawling workflow into several components responsible for fetching, parsing, and saving data. Tasks are managed through queues, allowing different parts of the crawler to process work asynchronously and efficiently. PSpider defines a set of modules and utility classes that help developers manage crawling tasks, filter URLs, and process scraped content. ...
