Search Results for "python-kinterbasdb" - Page 2
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Showing 147 open source projects for "python-kinterbasdb"
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Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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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.
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Digraph3
A collection of python3 modules for Algorithmic Decision Theory
This collection of Python3 modules provides a large range of implemented decision aiding algorithms useful in the field of outranking digraphs based Multiple Criteria Decision Aid (MCDA), especially best choice, linear ranking and absolute or relative rating algorithms with multiple incommensurable criteria. Technical documentation and tutorials are available under the following link: https://digraph3.readthedocs.io/en/latest/ The tutorials introduce the main objects like digraphs,... -
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Gemi
PCR primers / probes design from multiple & degenerate sequences
...Gemi can be used for quantitative, real-time and conventional PCR (qPCR, rt-PCR, etc.), and Sanger sequencing. Gemi can parse large dataset of sequences efficiently. Python source code is available upon request. Milestone: The tool reached about 3000 downloads sine 2012. Article Gemi: PCR primers prediction from multiple alignments. Comparative and functional genomics 2012 PMID: https://www.ncbi.nlm.nih.gov/pubmed/23316117 A great review on designing primer, Gemi, and other tools: Designing degenerate primers: Overview, challenges, and computational methods. ... -
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Evolutionary Algorithm
Evolutionary Algorithm using Python
Evolutionary Algorithm is an educational Python project that demonstrates evolutionary computation techniques such as genetic algorithms, evolution strategies, and neuroevolution in a clear and accessible way. Rather than being a single monolithic library, this repository provides a series of self-contained examples showing how different population-based search methods solve optimization problems and adapt candidate solutions over generations. -
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Elementary Algorithms
Book of elementary algorithms and data structures
This book introduces elementary algorithms and data structure. It includes side-by-side comparison of purely functional realization and their imperative counterpart. From 2020/12, I started re-writing this book. The PDF can be downloaded for preview (EN, 中文). The 1st edition in Chinese (中文) was published in 2017. I recently switched my focus to the Mathematics of programming, the new book is also available in (github). To build the book in PDF format from the sources, you need the following... -
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MLPACK is a C++ machine learning library with emphasis on scalability, speed, and ease-of-use. Its aim is to make machine learning possible for novice users by means of a simple, consistent API, while simultaneously exploiting C++ language features to provide maximum performance and flexibility for expert users. * More info + downloads: https://mlpack.org * Git repo: https://github.com/mlpack/mlpack
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ImageAI
A python library built to empower developers
ImageAI is an easy-to-use Computer Vision Python library that empowers developers to easily integrate state-of-the-art Artificial Intelligence features into their new and existing applications and systems. It is used by thousands of developers, students, researchers, tutors and experts in corporate organizations around the world. You will find features supported, links to official documentation as well as articles on ImageAI. -
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Real-ESRGAN
Real-ESRGAN aims at developing Practical Algorithms
...The repository includes inference and training scripts, a model zoo with different pretrained models (including general and anime-oriented variants), and support for batch and arbitrary scaling, making it adaptable for diverse enhancement tasks. It emphasizes usability with utilities that handle alpha channels, gray/16-bit images, and tiled inference for large inputs, and can be run via Python scripts or portable executables. -
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AlphaTensor
AI discovers faster, efficient algorithms for matrix multiplication
...These contain implementations of the discovered matrix multiplication algorithms, tools to benchmark their real-world performance, proofs of nonequivalence among thousands of solutions, and methods for decomposing larger problems into smaller factorizations. Users can explore AlphaTensor’s discovered algorithms interactively using Colab notebooks or Python scripts. -
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GFPGAN
GFPGAN aims at developing Practical Algorithms
GFPGAN aims at developing Practical Algorithms for Real-world Face Restoration. Colab Demo for GFPGAN; (Another Colab Demo for the original paper model) Online demo: Huggingface (return only the cropped face) Online demo: Replicate.ai (may need to sign in, return the whole image). Online demo: Baseten.co (backed by GPU, returns the whole image). We provide a clean version of GFPGAN, which can run without CUDA extensions. So that it can run in Windows or on CPU mode. GFPGAN aims at developing... -
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Gym
Toolkit for developing and comparing reinforcement learning algorithms
Gym by OpenAI is a toolkit for developing and comparing reinforcement learning algorithms. It supports teaching agents, everything from walking to playing games like Pong or Pinball. Open source interface to reinforce learning tasks. The gym library provides an easy-to-use suite of reinforcement learning tasks. Gym provides the environment, you provide the algorithm. You can write your agent using your existing numerical computation library, such as TensorFlow or Theano. It makes no... -
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Reinforcement-learning
Implementation of Reinforcement Learning Algorithms. Python, OpenAI
...The project collects popular approaches such as dynamic programming, Monte Carlo methods, temporal difference learning, Q-learning, SARSA, deep Q-networks, and policy gradient techniques, often demonstrated with Python and OpenAI Gym environments so users can experiment with agents learning in simulated tasks. For each algorithm category, the repository pairs conceptual descriptions with runnable code and often illustrated exercises that help solidify understanding by bridging theory with practice. It’s structured to serve learners progressing from basic tabular methods to function approximation and deep learning extensions, making it suitable for students, researchers, or practitioners exploring reinforcement learning fundamentals. -
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Sudoku Maker is a generator for Sudoku number puzzles. It uses a genetic algorithm internally, so it can serve as an introduction to genetic algorithms. The generated Sudokus are usually very hard to solve -- good for getting rid of a Sudoku addiction.
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Clipper
Polygon and line clipping and offsetting library (C++, C#, Delphi)
This library is now obsolete and no longer being maintained. It has been superceded by my Clipper2 library - https://github.com/AngusJohnson/Clipper2. -
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LeetCode Python
LeetCode Solutions: A Record of My Problem Solving Journey
This repository is a comprehensive personal journal of LeetCode problem-solving journey. It includes detailed solutions with code, algorithm insights, data structure summaries, Anki flashcards, daily challenge logs, and future planning sections. -
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Real-ESRGAN ncnn Vulkan
NCNN implementation of Real-ESRGAN
...Unlike the standard PyTorch-based Real-ESRGAN code, this variant is written in C/C++ and designed to run efficiently on many platforms (including Windows, Linux, and possibly Android) without requiring heavy frameworks like CUDA or Python. It provides command-line tools for upscaling images with selected models, allowing users to specify input/output paths, scaling factors, tile sizes, and model names from a compressed model set, which is particularly helpful for larger images or automated workflows. The Vulkan backend enables fast execution on GPUs from different vendors (Intel/AMD/Nvidia) with broad support, making it suitable for non-Python environments, production systems, or performance-constrained setups. -
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Binarytree
Python library for studying Binary Trees
Binarytree is Python library that lets you generate, visualize, inspect and manipulate binary trees. Skip the tedious work of setting up test data, and dive straight into practicing algorithms. Heaps and BSTs (binary search trees) are also supported. Binarytree supports another representation which is more compact but without the indexing properties. -
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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 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 recognition dataset, RGB, depth, infrared, skeletal data. Split into background / evaluation sets for one-shot evaluation (in the extended dataset). -
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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. -
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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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scikit-opt
Genetic Algorithm, Particle Swarm Optimization, Simulated Annealing
scikit-opt is a Python library for solving optimization problems with evolutionary and swarm-intelligence algorithms. It includes genetic algorithms, particle swarm optimization, differential evolution, simulated annealing, ant colony optimization, immune algorithms, and artificial fish swarms. The package can address continuous objectives, constrained problems, and combinatorial tasks such as the traveling salesman problem. -
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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
...This book is interactive. While you can read it online as static content, it's better to use it as intended. It is written using Jupyter Notebook, which allows you to combine text, math, Python, and Python output in one place. -
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Zipline
Zipline, a Pythonic algorithmic trading library
...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 package. For a development installation (used to develop Zipline itself), create and activate a virtualenv, then run the etc/dev-install script. Please note that Zipline is not a community-led project. Zipline is maintained by the Quantopian engineering team, and we are quite small and often busy.
