Search Results for "automatic"
Sort By:
Showing 29 open source projects for "automatic"
View related business solutions-
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.
-
Grafana: The open and composable observability platformGrafana is the open source analytics & monitoring solution for every database.
-
1
Flama
Fire up your models with the flame
...The library builds on Starlette, and provides an easy-to-learn philosophy to speed up the building of highly performant GraphQL, REST and ML APIs. Besides, it comprises an ideal solution for the development of asynchronous and production-ready services, offering automatic deployment for ML models. -
2
Plaso
Super timeline all the things
Plaso (Plaso Langar Að Safna Öllu), or "super timeline all the things," is a Python-based engine designed for automatic creation of timelines in digital forensic investigations. It processes various log files and artifacts to generate a chronological sequence of events, aiding analysts in understanding system activities. -
3
Jupyter Notebook Tools for Sphinx
Sphinx source parser for Jupyter notebooks
nbsphinx is a Sphinx extension that provides a source parser for *.ipynb files. Custom Sphinx directives are used to show Jupyter Notebook code cells (and of course their results) in both HTML and LaTeX output. Un-evaluated notebooks – i.e. notebooks without stored output cells – will be automatically executed during the Sphinx build process. -
4
Requests
A simple, yet elegant, HTTP library.
Requests is the de facto HTTP library for Python—simple, elegant, and human-friendly. It wraps urllib3 to provide intuitive methods for sending HTTP/1.1 requests, handling sessions, cookies, redirects, authentication, proxies, and more. -
Spidergap: Top Rated 360 Degree Feedback SoftwareWith an intuitive interface, Spidergap makes it easy to customize feedback assessments, generate clear reports, and guide employees toward impactful growth. But you’re not just getting software—you’re gaining a team of 360° Feedback Experts to support your strategy, planning, and ROI measurement. Whether you’re running large-scale leadership programs or one-off employee reviews, Spidergap ensures feedback leads to real results. With Spidergap, personal development has never been more effective.
-
5
Shumai
Fast Differentiable Tensor Library in JavaScript & TypeScript with Bun
...It provides a high-performance framework for numerical computing and machine learning within modern JavaScript runtimes. Built on Bun and Flashlight, with ArrayFire as its numerical backend, Shumai brings GPU-accelerated tensor operations, automatic differentiation, and scientific computing tools directly to JavaScript developers. It allows seamless integration of machine learning, deep learning, and custom differentiable programs into web-based or server-side environments without relying on Python frameworks. The library supports matrix operations, gradient computation, and tensor conversions with intuitive APIs and near-native speed, thanks to Bun’s low-overhead FFI bindings. ... -
6
Lightweight' GAN
Implementation of 'lightweight' GAN, proposed in ICLR 2021
...The general recommendation is to use suitable augs for your data and as many as possible, then after some time of training disable the most destructive (for image) augs. You can turn on automatic mixed precision with one flag --amp. You should expect it to be 33% faster and save up to 40% memory. Aim is an open-source experiment tracker that logs your training runs, and enables a beautiful UI to compare them. -
7
Tenacity Python
Retrying library for Python
Tenacity is a Python library that enables automatic retrying of functions with customizable strategies. It replaces the now-deprecated retrying library and supports exponential backoff, fixed delays, stop and wait conditions, and exception filtering. Useful for network operations, API calls, or any unstable process, Tenacity helps increase reliability in Python applications by handling transient failures gracefully and robustly. -
8
PyOpenCL
OpenCL integration for Python, plus shiny features
PyOpenCL is a Python wrapper for the OpenCL framework, providing seamless access to parallel computing on CPUs, GPUs, and other accelerators. It enables developers to harness the full power of heterogeneous computing directly from Python, combining Python’s ease of use with the performance benefits of OpenCL. PyOpenCL also includes convenient features for managing memory, compiling kernels, and interfacing with NumPy, making it a preferred choice in scientific computing, data analysis, and... -
9
Tortoise ORM
Familiar asyncio ORM for python, built with relations in mind
Tortoise ORM is an easy-to-use asyncio ORM (Object Relational Mapper) for Python, inspired by Django's ORM. It is designed to work with asynchronous frameworks, providing a simple and familiar API for interacting with databases. Tortoise ORM supports various relational databases and is suitable for building high-performance web applications. -
Construction Management Software for subcontractorsPlexxis serves subcontractors who seek elite team cohesion and performance. Coupling cloud construction management software, on-premise and hosted solutions, we unite operations, estimating, accounting and field apps on a single technology stack that enables live feedback between bidding, field and finance while in-house services drive continuous adoption.
-
10
PennyLane
A cross-platform Python library for differentiable programming
A cross-platform Python library for differentiable programming of quantum computers. Train a quantum computer the same way as a neural network. Built-in automatic differentiation of quantum circuits, using the near-term quantum devices directly. You can combine multiple quantum devices with classical processing arbitrarily! Support for hybrid quantum and classical models, and compatible with existing machine learning libraries. Quantum circuits can be set up to interface with either NumPy, PyTorch, JAX, or TensorFlow, allowing hybrid CPU-GPU-QPU computations. ... -
11
SENAITE LIMS
SENAITE Meta Package
...Amongst other functionalities, SENAITE comes with highly-customizable workflows to drive users through the analytical process, easy-to-use UI for data registration, automatic import of results, data validation, and transition constraints. SENAITE can be easily integrated with instruments by using off-the-shell interfaces for data import and export. Custom interfacing is supported too. Import instrument results and avoid human errors in the carrying-over process. Reduce the turnaround time on results report delivery. ... -
12
redis-py
Redis Python client
redis-py is the official Python client for interacting with Redis, the in-memory data structure store. It supports all Redis commands and data types, making it easy to build caching, messaging, or real-time analytics features in Python applications. With both synchronous and asyncio support, redis-py is suited for modern Python projects and integrates smoothly into web frameworks, task queues, and backend services. -
13
sqlite-utils
Python CLI utility and library for manipulating SQLite databases
sqlite-utils is both a Python library and a command-line tool for creating, inspecting, and transforming SQLite databases with minimal boilerplate. It focuses on making common tasks like importing CSV/JSON, exploring tables, and running ad-hoc queries feel ergonomic and scriptable. As a CLI, it lets you build databases from structured data in one line, run queries against local files or in-memory databases, output results as JSON, CSV, or pretty tables, and configure full-text search. As a... -
14
Computer Science Flash Cards
Mini website for testing both general CS knowledge and enforce coding
...The cards distill topics like time and space complexity, classic data structures, algorithmic paradigms, operating systems, networking, and databases into short, testable prompts. They are designed for spaced-repetition style study so you can cycle frequently through fundamentals until recall feels automatic. Many cards point at canonical definitions or contrasts (e.g., stack vs. queue, BFS vs. DFS) to strengthen conceptual boundaries. The material favors clarity and breadth over exhaustive proofs, making it ideal for quick refreshers during a study plan. It complements longer resources by giving you a lightweight way to keep key concepts top of mind. -
15
RLax
Library of JAX-based building blocks for reinforcement learning agents
RLax (pronounced “relax”) is a JAX-based library developed by Google DeepMind that provides reusable mathematical building blocks for constructing reinforcement learning (RL) agents. Rather than implementing full algorithms, RLax focuses on the core functional operations that underpin RL methods—such as computing value functions, returns, policy gradients, and loss terms—allowing researchers to flexibly assemble their own agents. It supports both on-policy and off-policy learning, as well as... -
16
Robin-Stocks API Library
This is a library to use with Robinhood Financial App
...With this library, you can view information on stocks, options, and cryptocurrencies in real-time, create your own robo-investor or trading algorithm, and improve your programming skills. The supported APIs are Robinhood, Gemini, and TD Ameritrade. If you are contributing to this project and would like to use automatic testing for your changes, you will need to install pytest and pytest-dotenv. You will also need to fill out all the fields in .test.env. I recommend that you rename the file as .env once you are done adding in all your personal information. -
17
Alpa
Training and serving large-scale neural networks
Alpa is a system for training and serving large-scale neural networks. Scaling neural networks to hundreds of billions of parameters has enabled dramatic breakthroughs such as GPT-3, but training and serving these large-scale neural networks require complicated distributed system techniques. Alpa aims to automate large-scale distributed training and serving with just a few lines of code. -
18
quantitative
Quantized transactions python3
...The README and associated lessons walk the user through implementing algorithms, likely covering data handling, backtesting, and maybe simple trading logic. As an open-source educational resource, it’s designed for Python users interested in automatic trading, algorithmic strategies, and financial data analysis. -
19
CommandlineConfig
A library for users to write configurations in Python
...The library supports arbitrarily deep nested structures, type handling, enumerated value constraints, and even tuple types, which are common in ML experiment setups. It also includes features for automatic version checking and convenient help output, so users can quickly see available parameters and their descriptions via a -h flag. -
20
SVoice (Speech Voice Separation)
We provide a PyTorch implementation of the paper Voice Separation
SVoice is a PyTorch-based implementation of Facebook Research’s study on speaker voice separation as described in the paper “Voice Separation with an Unknown Number of Multiple Speakers.” This project presents a deep learning framework capable of separating mixed audio sequences where several people speak simultaneously, without prior knowledge of how many speakers are present. The model employs gated neural networks with recurrent processing blocks that disentangle voices over multiple... -
21
Nimporter
Compile Nim Extensions for Python On Import
Nimporter allows the seamless import of Nim code into Python projects, enabling the use of Nim's performance and syntax within Python applications. -
22
TensorNetwork
A library for easy and efficient manipulation of tensor networks
...It abstracts networks as nodes and edges, then compiles efficient contraction orders across multiple numeric backends so users can focus on model structure rather than index bookkeeping. Common network families (MPS/TT, PEPS, MERA, tree networks) are expressed with concise APIs that encourage experimentation and comparison. The library provides automatic path finding and cost estimation, exposing when contractions will explode in memory and suggesting better orders. Because it supports backends such as NumPy, TensorFlow, PyTorch, and JAX, the same model can run on CPUs, GPUs, or TPUs with minimal code changes. Tutorials and visualization helpers make it easier to understand how network topology affects expressive power and computational cost. -
23
Arraymancer
A fast, ergonomic and portable tensor library in Nim
Arraymancer is a tensor and deep learning library for the Nim programming language, designed for high-performance numerical computations and machine learning applications. -
24
gradslam
gradslam is an open source differentiable dense SLAM library
...However, learning representations for SLAM has been an open question, because traditional SLAM systems are not end-to-end differentiable. In this work, we present gradSLAM, a differentiable computational graph take on SLAM. Leveraging the automatic differentiation capabilities of computational graphs, gradSLAM enables the design of SLAM systems that allow for gradient-based learning across each of their components, or the system as a whole. -
25
fastNLP
fastNLP: A Modularized and Extensible NLP Framework
...Provide a variety of neural network components and recurrence models (covering tasks such as Chinese word segmentation, named entity recognition, syntactic analysis, text classification, text matching, metaphor resolution, summarization, etc.). Trainer provides a variety of built-in Callback functions to facilitate experiment recording, exception capture, etc. Automatic download of some datasets and pre-trained models.
