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Showing 2395 open source projects for "python accounting source code"
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The most trusted software in constructionHCSS provides easy-to-use software built for construction companies that want to win more work, work smarter, and boost profits. For nearly 40 years, we've helped heavy civil contractors, infrastructure builders, and utility companies improve operations, from estimating and project management to field tracking, equipment maintenance, and safety. Tools like HeavyBid, HeavyJob, and HCSS Safety are built for the field and designed to work together, giving your team real-time visibility, tighter cost control, and better job outcomes. With 45+ accounting integrations and customizable APIs, HCSS fits seamlessly into your tech stack. We regularly update our software based on feedback from real crews, ensuring it fits the way your team works. Backed by award-winning 24/7/365 support and a proven implementation process, HCSS helps reduce risk, cut inefficiencies, and deliver fast ROI. If you're ready to grow your business and gain a competitive edge, HCSS is the partner that gets you there.
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Planfix: Manage Projects, Team's Tasks and Business ProcessesPlanfix is like a souped-up business process management system for folks who really know their stuff. It's built to help you dive deeper and gives you more options than your run-of-the-mill project and task management systems. Best part? Even small businesses and non-profits can get in on the action.
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End-to-End Negotiator
Deal or No Deal? End-to-End Learning for Negotiation Dialogues
End-to-End Negotiator is a PyTorch-based research framework developed by Facebook AI Research to train neural agents capable of conducting strategic negotiations in natural language. The project implements the models presented in two key papers: “Deal or No Deal? End-to-End Learning for Negotiation Dialogues” and “Hierarchical Text Generation and Planning for Strategic Dialogue”. It enables agents to plan, reason, and communicate effectively to maximize outcomes in multi-turn negotiations... -
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MADDPG
Code for the MADDPG algorithm from a paper
MADDPG (Multi-Agent Deep Deterministic Policy Gradient) is the official code release from OpenAI’s paper Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments. The repository implements a multi-agent reinforcement learning algorithm that extends DDPG to scenarios where multiple agents interact in shared environments. Each agent has its own policy, but training uses centralized critics conditioned on the observations and actions of all agents, enabling learning in... -
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TCellXTalk
TCellXTalk Web-App from LP CSIC/UAB
TCellXTalk is a comprehensive database of experimentally detected phosphorylation, ubiquitination and acetylation sites in human T cells. The web-app at www.TCellXTalk.org makes TCellXTalk accessible from Internet, and enables the in silico prediction of potential co-modified peptides to facilitate their experimental detection, using targeted or directed mass spectrometry, for the study of protein post-translational modification cross-talk. More detailed information on TCellXTalk and... -
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micrograd
A tiny scalar-valued autograd engine and a neural net library
micrograd is a tiny, educational automatic differentiation engine focused on scalar values, built to show how backpropagation works end to end with minimal code. It constructs a dynamic computation graph as you perform math operations and then computes gradients by walking that graph backward, making it an approachable “from scratch” autograd reference. On top of the core autograd “Value” concept, the project includes a small neural network library that lets you define and train simple... -
Automate Proposals with AI in Microsoft Word.Automate your best practices, processes, and standards to guide your proposal writers, sales teams, and subject experts. And don’t worry, it’s so easy to use they will use it. We would love the opportunity to help you quantify the impact your business can expect from investing in Expedience Software. Click here to request a Return on Investment (ROI) calculation. In this 15-minute session, we will ask 20 simple questions to assess and grade your current proposal quality and scalability. Manual proposal processes are likely costing you far more than you realize. These models waste time and kill the productivity of proposal writers, sales team members, senior staff, and subject experts.
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Knock Knock
Get notified when your training ends
Knock Knock is a lightweight Python utility created by the Hugging Face team that allows developers to receive notifications when long-running machine learning tasks finish or fail. Training deep learning models often takes hours or even days, making it inconvenient for engineers to constantly monitor progress manually. The library solves this problem by adding simple decorators or command-line commands that automatically send notifications when a process completes or crashes. These alerts... -
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TensorNets
High level network definitions with pre-trained weights in TensorFlow
High level network definitions with pre-trained weights in TensorFlow (tested with 2.1.0 >= TF >= 1.4.0). Applicability. Many people already have their own ML workflows and want to put a new model on their workflows. TensorNets can be easily plugged together because it is designed as simple functional interfaces without custom classes. Manageability. Models are written in tf.contrib.layers, which is lightweight like PyTorch and Keras, and allows for ease of accessibility to every weight and... -
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PyZgoubi is an interface to the Zgoubi particle tracking code written in python. It aims to ease the use of Zgoubi by providing a simple interface to create beam line elements and particles, and to automate running and analysing of simulations.
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FuzzyWuzzy
Fuzzy string matching in Python
We’ve made it our mission to pull in event tickets from every corner of the internet, showing you them all on the same screen so you can compare them and get to your game/concert/show as quickly as possible. Of course, a big problem with most corners of the internet is labeling. One of our most consistently frustrating issues is trying to figure out whether two ticket listings are for the same real-life event (that is, without enlisting the help of our army of interns). To pick an example... -
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stage0
A set of minimal dependency bootstrap binaries
This is a set of manually created hex programs in a Cthulhu Path to madness fashion. Which only have the goal of creating a bootstrapping path to a C compiler capable of compiling GCC, with only the explicit requirement of a single 1 KByte binary or less. Additionally, all code must be able to be understood by 70% of the population of programmers. If the code can not be understood by that volume, it needs to be altered until it satisfies the above requirement. -
B2i offers full-service IR websites, widgets and pluginsB2i Technologies provides the most robust and versatile tools to manage your Corporate website, Investor Relations website and email communications. Our Investor Relations Software solutions work through automation and implements into existing systems with ease in only a few steps. Our solutions not only help you stay compliant but save valuable time while reporting and delivering critical financial data and press release activities to investors. B2i's Investor Relations Solution provides highly reliable and customizable data for corporate websites including press releases, stock data, charting, and SEC filings within SOX compliance standards. Our investor relations software displays real-time data on your website without requiring additional work on your behalf. Once you have completed your filings and press releases they are automatically loaded onto your website and formatted for easy access.
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mssqlproxy
Toolkit aimed to perform lateral movement in restricted environments
mssqlproxy is a toolkit aimed to perform lateral movement in restricted environments through a compromised Microsoft SQL Server via socket reuse. The client requires impacket and sysadmin privileges on the SQL server. The first step is to execute code in the SQL Server process context. As extended stored procedures are going to be deprecated in future versions of MSSQL, we pay attention to Microsoft recommendations and thus, use CLR assemblies instead. -
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ChainerRL
ChainerRL is a deep reinforcement learning library
ChainerRL (this repository) is a deep reinforcement learning library that implements various state-of-the-art deep reinforcement algorithms in Python using Chainer, a flexible deep learning framework. PFRL is the PyTorch analog of ChainerRL. ChainerRL has a set of accompanying visualization tools in order to aid developers' ability to understand and debug their RL agents. With this visualization tool, the behavior of ChainerRL agents can be easily inspected from a browser UI. Environments... -
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Python Bible Reading Module
Python Bible Reading Module is an open source python module.
Python Bible Reading Module ( PBRM ) is an open source python module. It's designed in python 3, but should be compatible with python 2 . This module allows you to easily import different versions of the bible into your code. -
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HDL Checker
Repurposing existing HDL tools to help writing better code
HDL Checker is a language server that wraps VHDL/Verilg/SystemVerilog tools that aims to reduce the boilerplate code needed to set things up. It supports Language Server Protocol or a custom HTTP interface; can infer the library VHDL files likely to belong to, besides working out mixed language dependencies, compilation order, interpreting some compiler messages and providing some (limited) static checks. Notice that currently, the unused reports has caveats, namely declarations with the... -
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PixelCNN
Code for the paper "PixelCNN++: A PixelCNN Implementation..."
PixelCNN is the official implementation from OpenAI of the autoregressive generative model described in the paper Conditional Image Generation with PixelCNN Decoders. It provides code for training and evaluating PixelCNN models on image datasets, focusing on conditional image modeling where pixels are generated sequentially based on the values of previously generated pixels. The repository demonstrates how to apply masked convolutions to enforce autoregressive dependencies and achieve... -
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CrypTen
A framework for Privacy Preserving Machine Learning
CrypTen is a research framework developed by Facebook Research for privacy-preserving machine learning built directly on top of PyTorch. It provides a secure and intuitive environment for performing computations on encrypted data using Secure Multiparty Computation (SMPC). Designed to make secure computation accessible to machine learning practitioners, CrypTen introduces a CrypTensor object that behaves like a regular PyTorch tensor, allowing users to seamlessly apply automatic... -
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QRCode-Generator
Application for QR Code generation.
This is a minimalistic application to generate QR Code. Enter the data and easily convert the data to QR Code. -
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textgenrnn
Easily train your own text-generating neural network
With textgenrnn you can easily train your own text-generating neural network of any size and complexity on any text dataset with a few lines of code. A modern neural network architecture that utilizes new techniques as attention-weighting and skip-embedding to accelerate training and improve model quality. Train on and generate text at either the character-level or word-level. Configure RNN size, the number of RNN layers, and whether to use bidirectional RNNs. Train on any generic input text... -
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Spinning Up in Deep RL
Educational resource to help anyone learn deep reinforcement learning
Welcome to Spinning Up in Deep RL! This is an educational resource produced by OpenAI that makes it easier to learn about deep reinforcement learning (deep RL). For the unfamiliar, reinforcement learning (RL) is a machine learning approach for teaching agents how to solve tasks by trial and error. Deep RL refers to the combination of RL with deep learning. At OpenAI, we believe that deep learning generally, and deep reinforcement learning specifically, will play central roles in the... -
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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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TensorFlow Machine Learning Cookbook
Code for Tensorflow Machine Learning Cookbook
TensorFlow Machine Learning Cookbook repository provides practical code examples and educational materials that accompany the book 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... -
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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... -
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Machine Learning with TensorFlow
Accompanying source code for Machine Learning with TensorFlow
Machine Learning with TensorFlow is an open repository containing the source code and practical examples that accompany the book Machine Learning with TensorFlow. The project provides numerous code samples demonstrating how to build machine learning models using the TensorFlow framework. These examples illustrate core machine learning concepts such as regression, classification, clustering, and neural networks through practical implementations. The repository includes implementations of... -
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deep-q-learning
Minimal Deep Q Learning (DQN & DDQN) implementations in Keras
The deep-q-learning repository authored by keon provides a Python-based implementation of the Deep Q-Learning algorithm — a cornerstone method in reinforcement learning. It implements the core logic needed to train an agent using Q-learning with neural networks (i.e. approximating Q-values via deep nets), setting up environment interaction loops, experience replay, network updates, and policy behavior. For learners and researchers interested in reinforcement learning, this repo offers a... -
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TensorFlow Course
Simple and ready-to-use tutorials for TensorFlow
This repository houses a highly popular (~16k stars) set of TensorFlow tutorials and example code aimed at beginners and intermediate users. It includes Jupyter notebooks and scripts that cover neural network fundamentals, model training, deployment, and more, with support for Google Colab. -
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Miasm
Reverse engineering framework in Python
The Miasm intermediate representation is used for multiple task: emulation through its jitter engine, symbolic execution, DSE, program analysis, but the intermediate representation can be a bit hard to read. We will present in this article new tricks Miasm has learned in 2018. Among them, the SSA/Out-of-SSA transformation, expression propagation and high-level operators can be joined to “lift” Miasm IR to a more human-readable language. We use graphviz to illustrate some graphs. Its layout...
