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Showing 123 open source projects for "compiler python linux"
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Premier Construction SoftwareRated #1 Construction Accounting Software by Forbes Advisor in 2022 & 2023. Our modern SAAS solution is designed to meet the needs of General Contractors, Developers/Owners, Homebuilders & Specialty Contractors.
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CountBitsSet
minimal benchmark code for Counting Set Bits (ones) in an Integer
I was curious how much better the Algorithms, pointed out by BitTwiddling Hacks, perform than a simple Lookup Table approach... Now I think, perhaps my little investigation is interesting for others too... PS: the parallel counting Algo is about 35% faster on average on my computers than a simple LUT based solution. Also this shows nicely how different a human brain compatible solution is to a binary machine optimal solution :-) In the meantime I added other Algorithms beside... -
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Rank-BM25
A Collection of BM25 Algorithms in Python
A collection of algorithms for querying a set of documents and returning the ones most relevant to the query. The most common use case for these algorithms is, as you might have guessed, to create search engines. -
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NTU RGB-D
Info and sample codes for "NTU RGB+D Action Recognition Dataset"
The “NTU RGB+D” repository provides access to a large-scale dataset for human action recognition (and its extension, NTU RGB+D 120). The dataset includes multiple modalities (RGB video, depth sequences, infrared video, 3D skeletal joint data) captured with multiple Kinect v2 cameras simultaneously. The repository also contains MATLAB / Python demo scripts for loading, visualizing, and processing skeleton data, mapping between modalities, and handling dataset structure. Multi-modal action... -
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KaHaShEr
File checksum generator and verifier.
KaHaShEr is an application to check the integrity of a file using MD5, SHA1, SHA256 and SHA512 checksum. Designed to be smart and easy to use, it includes a feature that can detect a hexadecimal value in the clipboard and automatically perform the verification while notifying you with a very expressive sound of the outcome of this verification. -
Turn more customers into advocates.The platform's advanced capabilities ensure companies get the most out of their referral programs. Leverage custom events, profiles, and attributes to enable dynamic, audience-specific referral experiences. Use first-party data to tailor customer segment messaging, rewards, and engagement strategies. Use our flexible APIs to build management capabilities and consumer experiences–headlessly or hybrid. We have all the tools you need to build scalable, secure, and high-performing referral programs.
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Detectron2
Next-generation platform for object detection and segmentation
Detectron2 is Facebook AI Research's next generation software system that implements state-of-the-art object detection algorithms. It is a ground-up rewrite of the previous version, Detectron, and it originates from maskrcnn-benchmark. It is powered by the PyTorch deep learning framework. Includes more features such as panoptic segmentation, Densepose, Cascade R-CNN, rotated bounding boxes, PointRend, DeepLab, etc. Can be used as a library to support different projects on top of it. We'll... -
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TA-Lib.git: Technical Analysis Library
Mirror of the TA-Lib project using a Git repository
This project is intended to provide Git access to the code of the original project, TA-Lib, which uses Subversion. It is intended for system integrators wishing to use TA-Lib in their Git-managed project through Git submodules or subtrees. No actual development is being done here; all development happens in the original project. -
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Kalman and Bayesian Filters in Python
Kalman Filter book using Jupyter Notebook
Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filters, and more. All exercises include solutions. Introductory text for Kalman and Bayesian filters. All code is written in Python, and the book itself is written using Juptyer Notebook so that you can run and modify the code in your browser. What better way to learn? This book teaches you how to... -
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Zipline
Zipline, a Pythonic algorithmic trading library
Zipline is a Pythonic algorithmic trading library. It is an event-driven system for backtesting. Zipline is currently used in production as the backtesting and live-trading engine powering Quantopian -- a free, community-centered, hosted platform for building and executing trading strategies. Quantopian also offers a fully managed service for professionals that includes Zipline, Alphalens, Pyfolio, FactSet data, and more. Installing Zipline is slightly more involved than the average Python... -
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Fun4Me
A package for functional annotation for metagenomes
This package includes a few programs for rapid functional annotation for metagenomic sequences, including, 1) Gene prediction by FragGeneScan; 2) Similarity search by RAPSearch2; 3) Functional annotation in GO (Gene Ontology) and EC (Enzyme Commission) based on similarity search results; 4) From EC to metabolic pathway reconstruction by MinPath. Inputs: Just sequencing reads (or assemblies) Outputs: Protein-coding genes (or gene fragments); similarity search; functional annotations... -
AI-powered conversation intelligence softwareEvery customer interaction is vital to your business success and revenue growth. With Jiminny’s AI-powered conversation intelligence software, we take recording, capturing, and meticulous analysis of call recordings to the next level. Unlock call analytics that provide actionable insights with our call tracking software, empowering you to identify what's working and what's not. Seamlessly support your biggest objectives across the entire business landscape with our innovative call tracking system.
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StructPie
A set of C libraries to implement data structures and algorithms
Struct-Pie (Structures Pie) is a set of C shared libraries to implement data structures and algorithms so that they can be used/integrated easily into C projects. LIFO & FIFO Stack, Binary Search Tree, Priority Queue and a Hash Table are implemented and included in this package. Future releases will have many other data structures. The hash table in this package uses separate chaining to avoid collision. In the "hash_table" directory, the hash table implementation uses linked lists.... -
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Pytholog
A logic programming tool and a logical database with a RESTful API
Pytholog Tool (Command line & API) An executable tool, built in python, that enables logic programming and prolog syntax through interactive shell that mimics prolog language and / or RESTful API that can be called from other applications. The tool is based on the python library pytholog which can be found here: https://github.com/mnoorfawi/pytholog The tool starts normally from the command line. Let's look at the arguments that can be specified while initiating the tool: $... -
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interactive-coding-challenges
120+ interactive Python coding interview challenges
Interactive Coding Challenges is a collection of practice problems designed to strengthen data structures, algorithms, and problem-solving skills. The repository emphasizes a learn-by-doing approach: you read a prompt, attempt a solution, and verify behavior with tests, often within notebooks or scripts. Problems span arrays, strings, stacks, queues, linked lists, trees, graphs, dynamic programming, and more, mirroring common interview themes. Many challenges include hints and reference... -
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Smart Algorithm
Repository implementing a variety of intelligent algorithms
Smart-Algorithm is a repository implementing a variety of intelligent / metaheuristic optimization algorithms (e.g. Genetic Algorithm, Ant Colony, Particle Swarm, Immune Algorithm). The implementations are provided in multiple languages (Java, Python, MATLAB). The repository’s aim is to offer reference implementations of “smart” algorithms for tasks like route planning, optimization, or algorithm learning. Particle Swarm Optimization (PSO) implementations in multiple languages. Immune... -
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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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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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Baselines
High-quality implementations of reinforcement learning algorithms
Unlike the other two, openai/baselines is not currently a maintained or prominent repo in the OpenAI organization (and I found no strong reference in OpenAI’s main GitHub). Historically, “baselines” repositories are often used for baseline implementations of reinforcement learning algorithms or reference models (e.g. in the RL domain). If there was an OpenAI “baselines” repo, it might have contained reference implementations for reinforcement learning or model policy baselines to compare new... -
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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... -
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Active Learning
Framework and examples for active learning with machine learning model
Active Learning is a Python-based research framework developed by Google for experimenting with and benchmarking various active learning algorithms. It provides modular tools for running reproducible experiments across different datasets, sampling strategies, and machine learning models. The system allows researchers to study how models can improve labeling efficiency by selectively querying the most informative data points rather than relying on uniformly sampled training sets. The main... -
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Code Catalog in Python
Algorithms and data structures for review for coding interview
code-catalog-python serves as a grab-bag of small, readable Python examples that illustrate common algorithms, data structures, and utility patterns. Each snippet aims to be self-contained and easy to study, with clear inputs, outputs, and the essential logic on display. 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... -
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Omniglot
Omniglot data set for one-shot learning
This repository hosts the Omniglot dataset for one-shot learning, containing handwritten characters across multiple alphabets along with stroke data. It includes both MATLAB and Python starter scripts (e.g. demo.m, demo.py) to illustrate how to load the images and stroke sequences and run baseline experiments (such as classification by modified Hausdorff distance). The dataset provides both an image representation of each character and the time-ordered stroke coordinates ([x, y, t]) for each... -
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Data Algorithm/leetcode/lintcode
Data Structure and Algorithm notes
This work is some notes of learning and practicing data structures and algorithms. Part I is a brief introduction of basic data structures and algorithms, such as, linked lists, stack, queues, trees, sorting and etc. This book notes about learning data structure and algorithms. It was written in Simplified Chinese but other languages such as English and Traditional Chinese are also working in progress. -
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Various tools for automating some trading operations on the most popular cryptocurrency exchanges.
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Charting tools, backtesting tools, and data visualization tools for the most popular cryptocurrencies.
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TextTeaser
TextTeaser is an automatic summarization algorithm
textteaser is an automatic text summarization algorithm implemented in Python. It extracts the most important sentences from an article to generate concise summaries that retain the core meaning of the original text. The algorithm uses features such as sentence length, keyword frequency, and position within the document to determine which sentences are most relevant. By combining these features with a simple scoring mechanism, it produces summaries that are both readable and informative.... -
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Pygorithm
A Python module for learning all major algorithms
A Python module to learn all the major algorithms on the go! Purely for educational purposes. If you are using Python 2.7 use pip instead. Depending on your permissions, you might need to use pip install, user pygorithm to install. To see all the available functions in a module, you can just type help() with the module name as an argument.
