Search Results for "aras-common"

LASS : Library of Assembled Shared Source. Library of C++ code for scientific purposes.

...ImageAI provides API to recognize 1000 different objects in a picture using pre-trained models that were trained on the ImageNet-1000 dataset. The model implementations provided are SqueezeNet, ResNet, InceptionV3 and DenseNet. ImageAI provides API to detect, locate and identify 80 most common objects in everyday life in a picture using pre-trained models that were trained on the COCO Dataset.

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.

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...

...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 solutions so you can compare approaches and learn idiomatic patterns. The structure encourages incremental improvement—start with a brute-force idea, then refine to optimal time and space complexity. It serves both as a self-study path and as a warm-up bank for interview prep or coding katas.

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 about edge performance. ...

pyhanlp is a Python interface for HanLP (Han Language Processing) that lets you use a mature Java-based NLP toolkit from Python workflows without rebuilding the underlying algorithms. It is commonly used for Chinese-language NLP tasks where you want production-grade tokenization and linguistic analysis, but still want the convenience of Python scripting. The project focuses on making HanLP’s capabilities accessible through a Python-friendly API surface, so you can integrate NLP steps into...

Algorithms in Python is a collection of algorithm and data structure implementations (primarily in Python) meant to serve as both learning material and reference code for engineers. It includes code for graph algorithms, heap data structures, stacks, queues, and more — each implemented cleanly so learners can trace logic and adapt for their problems. The repository is particularly useful for people preparing for competitive programming, job interviews, or building a foundational...

pycrc is an easy to use CRC (cyclic redundancy check) calculator and C source code generator. The generated source code can be optimized for simplicity, speed or space. pycrc contains a long parameter list of common CRC models. The program is self contained and does not require installation. Apart from a python installation, it does not require other libraries to be installed.

Reader xpdl documents, BPM tools, convert in db project structure.

eBarter froms trades from commitments. It measures economic values without the need of a common value standard; distributes fairly the gain produced between participants and gives the preference to trades where participants have the weakest requirements.

The LisBON Framework is an adaptable framework for developing new parallel Memetic Algorithms (hybrid search algorithms for efficiently solving optimisation problems).