Search Results for "high" - Page 3
Sort By:
Showing 68 open source projects for "high"
View related business solutions-
Stop vibe-debugging.AppSignal's MCP server hands Claude, Cursor, or Zed your real errors, traces, and the deploy that shipped them. AI writes the fix; you review the diff.
-
$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
AdaNet
Fast and flexible AutoML with learning guarantees
AdaNet is a TensorFlow framework for fast and flexible AutoML with learning guarantees. AdaNet is a lightweight TensorFlow-based framework for automatically learning high-quality models with minimal expert intervention. AdaNet builds on recent AutoML efforts to be fast and flexible while providing learning guarantees. Importantly, AdaNet provides a general framework for not only learning a neural network architecture but also for learning to the ensemble to obtain even better models. At each iteration, it measures the ensemble loss for each candidate, and selects the best one to move onto the next iteration. ... -
2
Forecasting Best Practices
Time Series Forecasting Best Practices & Examples
Time series forecasting is one of the most important topics in data science. Almost every business needs to predict the future in order to make better decisions and allocate resources more effectively. This repository provides examples and best practice guidelines for building forecasting solutions. The goal of this repository is to build a comprehensive set of tools and examples that leverage recent advances in forecasting algorithms to build solutions and operationalize them. Rather than... -
3
Top Deep Learning Projects
A list of popular github projects related to deep learning
...Rather than being a library itself, it serves as a curated roadmap and reference guide for anyone exploring the deep learning ecosystem — from beginners to experienced practitioners. By aggregating high-star projects across frameworks (TensorFlow, PyTorch), tools (computer vision, NLP, reinforcement learning), tutorials, and research code, it helps users quickly discover reputable and well-maintained repositories. This way one can survey state-of-the-art projects, find learning resources, or pick stable libraries for production — without manually sifting through hundreds of repos. ... -
4
Graph Nets library
Build Graph Nets in Tensorflow
Graph Nets, developed by Google DeepMind, is a Python library designed for constructing and training graph neural networks (GNNs) using TensorFlow and Sonnet. It provides a high-level, flexible framework for building neural architectures that operate directly on graph-structured data. A graph network takes graphs as inputs, consisting of edges, nodes, and global attributes, and produces updated graphs with modified feature representations at each level. This library implements the foundational ideas from DeepMind’s paper “Relational Inductive Biases, Deep Learning, and Graph Networks”, offering tools to explore relational reasoning and message-passing neural networks. ... -
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
12306 Ticket Buying Assistant
12306 Smart ticket swiping, ticket booking
12306 is an automation and ticket-purchasing tool designed to interact with China’s official railway booking system, providing users with a programmatic way to search, reserve, and purchase train tickets. The project replicates the workflow of the official platform while adding automation features that help users secure tickets in high-demand scenarios. It supports querying schedules, checking seat availability, and performing booking actions through scripts, which reduces the need for manual interaction. The system is particularly useful during peak travel periods when tickets sell out quickly, as it can continuously monitor availability and attempt purchases automatically. ... -
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
MLBox
MLBox is a powerful Automated Machine Learning python library
MLBox is a powerful Automated Machine Learning python library. Fast reading and distributed data preprocessing/cleaning/formatting. Highly robust feature selection and leak detection. Accurate hyper-parameter optimization in high-dimensional space. State-of-the-art predictive models for classification and regression (Deep Learning, Stacking, LightGBM,...) Prediction with model interpretation. MLBox has been developed and used by many active community members. Your help is very valuable to make it better for everyone. -
8
SFD
S³FD: Single Shot Scale-invariant Face Detector, ICCV, 2017
S³FD (Single Shot Scale-invariant Face Detector) is a real-time face detection framework designed to handle faces of various sizes with high accuracy using a single deep neural network. Developed by Shifeng Zhang, S³FD introduces a scale-compensation anchor matching strategy and enhanced detection architecture that makes it especially effective for detecting small faces—a long-standing challenge in face detection research. The project builds upon the SSD framework in Caffe, with modifications tailored for face detection tasks. ... -
9
TensorFlow World
Simple and ready-to-use tutorials for TensorFlow
...The question that should be asked is why has this repository been created when there are so many other tutorials about TensorFlow available on the web? Deep Learning is in very high interest these days - there's a crucial need for rapid and optimized implementations of the algorithms and architectures. TensorFlow is designed to facilitate this goal. The strong advantage of TensorFlow is it flexibility in designing highly modular models which can also be a disadvantage for beginners since a lot of the pieces must be considered together when creating the model. -
Ship Agents FasterGemini Enterprise Agent Platform lets you rapidly build, scale, govern and optimize production-ready agents grounded in your organization's data. The platform enables developers to build custom or pre-built agents for virtually any use case. New customers get $300 in free credits.
-
10
gevent
Coroutine-based concurrency library for Python
gevent is a coroutine -based Python networking library that uses greenlet to provide a high-level synchronous API on top of the libev or libuv event loop. gevent is inspired by eventlet but features a more consistent API, simpler implementation and better performance. Read why others use gevent and check out the list of the open source projects based on gevent. Since version 1.1, gevent is maintained by Jason Madden for NextThought with help from the contributors and is licensed under the MIT license. ... -
11
PrettyTensor
Pretty Tensor: Fluent Networks in TensorFlow
Pretty Tensor is a high-level API built on top of TensorFlow that simplifies the process of creating and managing deep learning models. It wraps TensorFlow tensors in a chainable object syntax, allowing developers to build multi-layer neural networks with concise and readable code. Pretty Tensor preserves full compatibility with TensorFlow’s core functionality while providing syntactic sugar for defining complex architectures such as convolutional and recurrent networks. -
12
PyCNN
Image Processing with Cellular Neural Networks in Python
...Image Processing is one of its applications. CNN processors were designed to perform image processing; specifically, the original application of CNN processors was to perform real-time ultra-high frame-rate (>10,000 frame/s) processing unachievable by digital processors. -
13
What is QPF 2.6 ? QPF 2.6 (or Quantum Programming framework 2.6) is a free simple and easy to use framework dedicated to supporting programmers who are developing software for the D-wave one series of quantum computers.
-
14
edumath
Python Module
edumath is a python module. You can do calculations of advance topics of mathematics of high school. In intial release v 1.0 it contains 28 functions for performing calculations. This is windows installer. Just download, read documentation on github and use it in your own projects. I started writing this module from 05-04-2014. I covered three topics of high school - Matrices, Progression and Vector Algebra. I am constanly working on edumath. -
15
FlyPDF is a shared object library (.so) which allows to generate PDF files without using any PDF library as dependency. You may use it for any kind of usage and modify it to suit your needs. FlyPDF has other advantages: high level functions.
-
16
Fast cython implementation of trie data structure for Python. Development is inactive, but moved to: http://github.com/martinkozak/cytrie.
-
17
PROTON
High-level python framework that facilitates rapid server-side develop
PROTON is a high-level Python framework that facilitates rapid server-side development with clean & pragmatic design. Thanks for checking it out! PROTON aims at easing server-side development for all Python enthusiasts. Essentially, by running a shell command, developer will auto generate necessary Model, Controller and APIs! All of this with connectivity to Transactional Databases (PROTON supports Postgresql, MySQL & SQL Server),caching (Redis middleware), Auto generated OpenAPI specs & descriptive logging! ... -
18
CloudTierSDK
CloudTier Storage Tiering SDK
The CloudTier Storage Tiering SDK is a Hierarchical Storage Management (HSM) file system filter driver development kit. It implements a data storage strategy that automatically migrates data between high-cost and low-cost storage media, optimizing storage efficiency and reducing both capital and operational expenses. This SDK offers a simple and cost-effective solution to seamlessly integrate your on-premises storage infrastructure with cloud storage. The migration of files to the cloud happens transparently and securely, with no disruption to existing applications or infrastructure. ...
