Search Results for "performance" - Page 33
Sort By:
Showing 1009 open source projects for "performance"
View related business solutions-
$300 Free Credits to Build on Google CloudStart your next project with $300 in free Google Cloud credit. Spin up VMs, run containers, query petabytes in BigQuery, or build agents with Gemini Enterprise Agent Platform. Once your credits are used, keep building with 20+ always-free tier products including Compute Engine, Cloud Storage, GKE, and Cloud Run functions. No commitment required—just sign up and start building.
-
$300 Free Credits for Your Google Cloud ProjectsLaunch your next project with $300 in free Google Cloud credits—no strings attached. Test, build, and deploy without risk. Use your credits across the entire Google Cloud platform to find what works best for your needs. After your credits are used, continue with always-free tier services. Only pay when you're ready to scale. Sign up in minutes and start exploring.
-
1
Budou
Budou is an auto organizer tool for beautiful line breaking in CJK
Budou is a Python library developed by Google to improve web typography for CJK (Chinese, Japanese, Korean) languages by producing semantically meaningful line breaks. Unlike English, CJK scripts lack spaces or hyphenation cues, often resulting in awkward or unreadable text wrapping on web pages. Budou addresses this issue by segmenting sentences into logical lexical chunks and wrapping each chunk in non-breaking HTML <span> tags. These spans can be styled with CSS to ensure smooth, visually... -
2
Torchreid
Deep learning person re-identification in PyTorch
...Under the same folder, you can find the tensorboard file. Different from the same-domain setting, here we replace random_erase with color_jitter. This can improve the generalization performance on the unseen target dataset. -
3
Python Patterns
A collection of design patterns/idioms in Python
Python-Patterns is a repository collecting implementations of many classical design patterns and idioms, written in Python. It serves as an educational resource: showing how to implement creational, structural, behavioral, testability, and other patterns in a Pythonic style (or sometimes less so), illustrating trade-offs, different styles, and use cases. It’s intended for learners or developers interested in software architecture or design, rather than as a production library. Includes... -
4
MatchZoo
Facilitating the design, comparison and sharing of deep text models
...Make use of MatchZoo customized loss functions and evaluation metrics. Initialize the model, fine-tune the hyper-parameters. Generate pair-wise training data on-the-fly, evaluate model performance using customized callbacks on validation data. MatchZoo is dependent on Keras and Tensorflow. -
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.
-
5
AutoBench
This program is a benchmark site data extraction util program
This program is a program that extracts the latest CPU, GPU, Drive and RAM performance scores and rankings from benchmark sites. The Output Data is saved as a csv, xlsx and xls file. CPU information is written by model name and score. GPU information is written by model name and score. Drive information is written by model name and score. RAM information is written by model name and score. -
6
TF Quant Finance
High-performance TensorFlow library for quantitative finance
TF Quant Finance is a high-performance library of quantitative finance components built on TensorFlow, aimed at research and production workloads. It implements pricing engines, risk measures, stochastic models, optimizers, and random number generators that are differentiable and vectorized for accelerators. Users can value options and fixed-income instruments, simulate paths, fit curves, and calibrate models while leveraging TensorFlow’s jit compilation and automatic differentiation. ... -
7
hug
Embrace the APIs of the future. For developing APIs
...Make developing a Python-driven API as succinct as a written definition. The framework should encourage code that self-documents. It should be fast. A developer should never feel the need to look somewhere else for performance reasons. Writing tests for APIs written on-top of hug should be easy and intuitive. Magic done once, in an API framework, is better than pushing the problem set to the user of the API framework. Be the basis for next-generation Python APIs, embracing the latest technology. -
8
I3D models trained on Kinetics
Convolutional neural network model for video classification
Kinetics-I3D, developed by Google DeepMind, provides trained models and implementation code for the Inflated 3D ConvNet (I3D) architecture introduced in the paper “Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset” (CVPR 2017). The I3D model extends the 2D convolutional structure of Inception-v1 into 3D, allowing it to capture spatial and temporal information from videos for action recognition. This repository includes pretrained I3D models on the Kinetics dataset, with... -
9
AET
Detects visual changes on websites and performs page health checks
AET is a system that detects visual changes on websites and performs basic page health checks (like w3c compliance, accessibility, HTTP status codes, JS Error checks and others). AET is designed as a flexible system that can be adapted and tailored to the regression requirements of a given project. The tool has been developed to aid front-end client-side layout regression testing of websites or portfolios, in essence assessing the impact or change of a website from one snapshot to the next. -
Our Free Plans just got better! | Auth0You asked, we delivered! Auth0 is excited to expand our Free and Paid plans to include more options so you can focus on building, deploying, and scaling applications without having to worry about your security. Auth0 now, thank yourself later.
-
10
bristoSOFT Contacts
bristoSOFT Contacts is group oriented contact management software.
bristoSOFT Contacts is a group oriented contact management software application written in Python, PyQt and PostgreSQL based on MVC software architecture. All contacts include email, telephone, address, title, name, company and also include notes, files, integrated google maps, activities such as phone calls, appointments, messaging, calendar. Contacts is a novel project with cutting edge technology. -
11
AIAlpha
Use unsupervised and supervised learning to predict stocks
AIAlpha is a machine learning project focused on building predictive models for financial markets and algorithmic trading strategies. The repository explores how artificial intelligence techniques can analyze historical financial data and generate predictions about asset price movements. It provides a research-oriented environment where users can experiment with data processing pipelines, model training workflows, and quantitative trading strategies. The project typically involves collecting... -
12
maskrcnn-benchmark
Fast, modular reference implementation of Instance Segmentation
Mask R-CNN Benchmark is a PyTorch-based framework that provides high-performance implementations of object detection, instance segmentation, and keypoint detection models. Originally built to benchmark Mask R-CNN and related models, it offers a clean, modular design to train and evaluate detection systems efficiently on standard datasets like COCO. The framework integrates critical components—region proposal networks (RPNs), RoIAlign layers, mask heads, and backbone architectures such as ResNet and FPN—optimized for both accuracy and speed. ... -
13
Coach
Enables easy experimentation with state of the art algorithms
Coach is a python framework that models the interaction between an agent and an environment in a modular way. With Coach, it is possible to model an agent by combining various building blocks, and training the agent on multiple environments. The available environments allow testing the agent in different fields such as robotics, autonomous driving, games and more. It exposes a set of easy-to-use APIs for experimenting with new RL algorithms and allows simple integration of new environments... -
14
pytorch-examples
Simple examples to introduce PyTorch
...It also serves as a quick reference for common patterns and techniques used in deep learning workflows. The project aligns with PyTorch’s philosophy of combining usability with performance and flexibility. Overall, pytorch-examples is an essential learning resource for anyone working with PyTorch. -
15
Drauger OS
Ubuntu-based Linux Gaming OS
Drauger OS is an Ubuntu-based Linux desktop gaming distribution that ships with many modifications and optimizations over stock Ubuntu that are intended to improve gaming performance and the gaming experience. From simple changes such as swapping Gnome out for the light-weight Xfce Desktop Environment and using a dark GTK theme by default, to more complex changes such as using a kernel compiled in-house and replacing PulseAudio with Pipewire. Drauger OS is built from the ground up with our primary focus on performance. ... -
16
RefineNet
RefineNet: Multi-Path Refinement Networks
...It provides trained models for datasets such as PASCAL VOC 2012, Cityscapes, NYUDv2, Person_Parts, PASCAL_Context, SUNRGBD, and ADE20k, with versions based on ResNet-101 and ResNet-152 backbones. The repository supports both single-scale and multi-scale prediction, with scripts for training, testing, and evaluating segmentation performance. While this codebase is specific to MATLAB and MatConvNet, a PyTorch implementation and lighter-weight variants are also available from the community. -
17
Imogen
GPU Texture Generator
Imogen is a real-time, node-based procedural texture generation tool aimed at artists, developers, and shader enthusiasts. It allows users to build complex material textures using a graph-based interface, combining operations like blending, noise, filters, and color correction in a non-destructive workflow. Built with Vulkan and ImGui, Imogen provides immediate visual feedback and supports GPU acceleration for high-resolution texture output. It's particularly useful in game development, VFX,... -
18
Open|SpeedShop
Open|SpeedShop is an open source multi platform Linux performance tool
Open|SpeedShop is an open source multi platform Linux performance tool which is targeted to support performance analysis of applications running on both single node and large scale IA64, IA32, EM64T, AMD64, PPC, Blue Gene, ARM and Cray platforms. -
19
pyfolio
Portfolio and risk analytics in Python
pyfolio is a Python library for performance and risk analysis of financial portfolios developed by Quantopian Inc. It works well with the Zipline open source backtesting library. At the core of pyfolio is a so-called tear sheet that consists of various individual plots that provide a comprehensive image of the performance of a trading algorithm. Here's an example of a simple tear sheet analyzing a strategy. -
20
TGAN
Generative adversarial training for generating synthetic tabular data
We are happy to announce that our new model for synthetic data called CTGAN is open-sourced. The new model is simpler and gives better performance on many datasets. TGAN is a tabular data synthesizer. It can generate fully synthetic data from real data. Currently, TGAN can generate numerical columns and categorical columns. TGAN has been developed and runs on Python 3.5, 3.6 and 3.7. Also, although it is not strictly required, the usage of a virtualenv is highly recommended in order to avoid interfering with other software installed in the system where TGAN is run. ... -
21
Green Recorder
A simple screen recorder for Linux desktop
...The application allows users to record full screens or specific areas, making it suitable for tutorials and demonstrations. It includes options for selecting audio sources and controlling frame rates to balance quality and performance. green-recorder is designed to be lightweight and user-friendly, minimizing system overhead during recording sessions. It also supports Wayland and Xorg environments, ensuring compatibility across different Linux setups. Overall, it offers an accessible solution for screen recording with essential customization options. -
22
NeuroNER
Named-entity recognition using neural networks
...Train the neural network that performs the NER. During the training, NeuroNER allows monitoring of the network. Evaluate the quality of the predictions made by NeuroNER. The performance metrics can be calculated and plotted by comparing the predicted labels with the gold labels. -
23
Easy-TensorFlow
Simple and comprehensive tutorials in TensorFlow
...Furthermore, since most of the developers are using TensorFlow for code development, having hands-on on TensorFlow is a necessity these days. Tensorboard is a powerful visualization suite that is developed to track both the network topology and performance, making debugging even simpler. -
24
Tensorpack
A Neural Net Training Interface on TensorFlow, with focus on speed
...Your training can probably gets faster if written with Tensorpack. Scalable data-parallel multi-GPU / distributed training strategy is off-the-shelf to use. Squeeze the best data loading performance of Python with tensorpack.dataflow. Symbolic programming (e.g. tf.data) does not offer the data processing flexibility needed in research. Tensorpack squeezes the most performance out of pure Python with various auto parallelization strategies. There are too many symbolic function wrappers already. Tensorpack includes only a few common layers. ... -
25
Code Catalog in Python
Algorithms and data structures for review for coding interview
...The catalog format lets you scan for an example, copy it, and adapt it to your use case without wading through a large framework. It favors clarity over micro-optimizations so learners can grasp the idea before worrying about edge performance. Over time it becomes a personal cookbook of solutions you can remix across projects. This approach is especially helpful when you need a quick refresher on a technique you haven’t used in a while.
