Search Results for "python-kinterbasdb" - Page 17
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Showing 625 open source projects for "python-kinterbasdb"
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pbxproj
A python module to manipulate XCode projects
...The file is usually called project.pbxproj and can be found inside the .xcodeproj bundle. Because some tasks cannot be done by clicking on a UI or opening Xcode to do it for you, this Python module lets you automate the modification process. The typical tasks with an Xcode project are adding files to the project and setting some standard compilation flags. -
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libpostal
A C library for parsing/normalizing street addresses around the world
A C library for parsing/normalizing street addresses around the world. Powered by statistical NLP and open geo data. libpostal is a C library for parsing/normalizing street addresses around the world using statistical NLP and open data. The goal of this project is to understand location-based strings in every language, everywhere. Addresses and the locations they represent are essential for any application dealing with maps (place search, transportation, on-demand/delivery services,... -
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Nerfies
This is the code for Deformable Neural Radiance Fields
Nerfies demonstrates deformation-aware neural radiance fields that reconstruct and render dynamic, real-world scenes from casual video. Instead of assuming a static world, the method learns a canonical space plus a deformation field that maps changing poses or expressions back to that space during training. This lets the system generate photorealistic novel views of nonrigid subjects—faces, bodies, cloth—while preserving fine detail and consistent lighting. The training pipeline handles... -
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Minkowski Engine
Auto-diff neural network library for high-dimensional sparse tensors
The Minkowski Engine is an auto-differentiation library for sparse tensors. It supports all standard neural network layers such as convolution, pooling, unspooling, and broadcasting operations for sparse tensors. The Minkowski Engine supports various functions that can be built on a sparse tensor. We list a few popular network architectures and applications here. To run the examples, please install the package and run the command in the package root directory. Compressing a neural network to... -
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PyG2Plot
Python3 binding Plotting Library
PyG2Plot is a Python 3 binding for AntV G2Plot, an interactive and responsive charting library. It lets Python users create statistical charts through a small amount of code while relying on G2Plot’s grammar-of-graphics foundation. The library is inspired by pyecharts and is designed to make web-based charts available from Python workflows. Users create a Plot instance, set chart options, and render the result as an HTML file, HTML string, notebook preview, or JupyterLab output. ... -
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Big List of Naughty Strings
List of strings which have a high probability of causing issues
The Big List of Naughty Strings is a community-maintained catalog of “gotcha” inputs that commonly break software, from unusual Unicode to SQL and script injection payloads. It exists so developers and QA engineers can easily test edge cases that normal test data would miss, such as zero-width characters, right-to-left marks, emojis, foreign alphabets, and long or malformed strings. By throwing these strings at forms, APIs, databases, and UIs, teams can discover encoding bugs, sanitizer... -
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earthengine-py-notebooks
A collection of 360+ Jupyter Python notebook examples
earthengine-py-notebooks is a comprehensive collection of hundreds of Jupyter Python notebooks that serve as examples and tutorials for using the Google Earth Engine Python API. These notebooks are organized into thematic areas such as image processing, machine learning, visualization, filtering, and asset management, exposing users to real geospatial analysis tasks. The repository makes it easier to explore Earth Engine’s large geospatial data catalog, interactively display map layers, and generate visual insights without the need for external GIS software by leveraging interactive widgets and mapping libraries. ... -
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BMC
Notes on Scientific Computing for Biomechanics
This repository is a collection of lecture notes and code on scientific computing and data analysis for Biomechanics and Motor Control. -
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Brain AutoML
Google Brain AutoML
...Google Brain researchers have introduced a new way of programming automated machine learning (AutoML) based on symbolic programming. The researchers also proposed PyGlove, a general symbolic programming library for Python, to implement the symbolic formulation of AutoML. AutoML, designed to fill the machine learning industry’s talent gap, is gaining traction among various organizations. -
Ship Agents FasterGemini Enterprise Agent Platform lets you rapidly build, scale, govern and optimize production-ready agents grounded in your organization's data. The platform enables developers to build custom or pre-built agents for virtually any use case. New customers get $300 in free credits.
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Awesome Graph Classification
Graph embedding, classification and representation learning papers
A collection of graph classification methods, covering embedding, deep learning, graph kernel and factorization papers with reference implementations. Relevant graph classification benchmark datasets are available. Similar collections about community detection, classification/regression tree, fraud detection, Monte Carlo tree search, and gradient boosting papers with implementations. -
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BeaEngine 5
BeaEngine disasm project
BeaEngine is a C library designed to decode instructions from 16-bit, 32-bit and 64-bit intel architectures. It includes standard instructions set and instructions set from FPU, MMX, SSE, SSE2, SSE3, SSSE3, SSE4.1, SSE4.2, VMX, CLMUL, AES, MPX, AVX, AVX2, AVX512 (VEX & EVEX prefixes), CET, BMI1, BMI2, SGX, UINTR, KL, TDX and AMX extensions. If you want to analyze malicious codes and more generally obfuscated codes, BeaEngine sends back a complex structure that describes precisely the... -
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gradslam
gradslam is an open source differentiable dense SLAM library
gradslam is an open-source framework providing differentiable building blocks for simultaneous localization and mapping (SLAM) systems. We enable the usage of dense SLAM subsystems from the comfort of PyTorch. The question of “representation” is central in the context of dense simultaneous localization and mapping (SLAM). Newer learning-based approaches have the potential to leverage data or task performance to directly inform the choice of representation. However, learning representations... -
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algo
50 Code Implementations You Must Know About Data Structures
...More advanced examples address backtracking, divide-and-conquer methods, dynamic programming, shortest paths, topological sorting, caches, and priority queues. Solutions are available across numerous languages, including C, C++, Java, Go, Python, JavaScript, Rust, Swift, Kotlin, and TypeScript. This multilingual layout helps learners compare syntax and implementation choices while studying the same concepts. The repository is well suited to interview preparation, classroom exercises, and deliberate coding practice. -
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NLP Architect
A model library for exploring state-of-the-art deep learning
NLP Architect is an open-source Python library for exploring state-of-the-art deep learning topologies and techniques for optimizing Natural Language Processing and Natural Language Understanding neural networks. The library includes our past and ongoing NLP research and development efforts as part of Intel AI Lab. NLP Architect is designed to be flexible for adding new models, neural network components, data handling methods, and for easy training and running models. -
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Hack-Tools
Hack tools
hack-tools is a collection of various hacking tools and utilities. It serves as a comprehensive toolkit for penetration testers and cybersecurity enthusiasts, encompassing a wide range of functionalities. -
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TFLearn
Deep learning library featuring a higher-level API for TensorFlow
TFlearn is a modular and transparent deep learning library built on top of Tensorflow. It was designed to provide a higher-level API to TensorFlow in order to facilitate and speed up experimentations while remaining fully transparent and compatible with it. Easy-to-use and understand high-level API for implementing deep neural networks, with tutorials and examples. Fast prototyping through highly modular built-in neural network layers, regularizers, optimizers, and metrics. Full transparency... -
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fastNLP
fastNLP: A Modularized and Extensible NLP Framework
fastNLP is a lightweight framework for natural language processing (NLP), the goal is to quickly implement NLP tasks and build complex models. A unified Tabular data container simplifies the data preprocessing process. Built-in Loader and Pipe for multiple datasets, eliminating the need for preprocessing code. Various convenient NLP tools, such as Embedding loading (including ELMo and BERT), intermediate data cache, etc.. Provide a variety of neural network components and recurrence models... -
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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. -
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StructPie
A set of C libraries to implement data structures and algorithms
...While in "HashBSTree" directory, a hash table with a binary tree in each index is implemented for faster lookup in large data. The stack, the tree and the hash table accept int, float and char* data type To look at the python library : https://github.com/mnoorfawi/struct-pie -
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SentEval
A python tool for evaluating the quality of sentence embeddings
SentEval is a standardized toolkit for evaluating sentence embeddings across a wide spectrum of downstream tasks and probing tests. It defines a simple interface—provide an encoder function from sentences to vectors—and then runs consistent training/evaluation loops for tasks like sentiment, entailment, paraphrase, and semantic textual similarity. The suite also contains linguistic probing tasks that illuminate what properties embeddings capture, such as tense, word order, or syntactic... -
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SageMaker MXNet Training Toolkit
Toolkit for running MXNet training scripts on SageMaker
...For the Dockerfiles used for building SageMaker MXNet Containers, see AWS Deep Learning Containers. For information on running MXNet jobs on Amazon SageMaker, please refer to the SageMaker Python SDK documentation. With the SDK, you can train and deploy models using popular deep learning frameworks Apache MXNet and TensorFlow. You can also train and deploy models with Amazon algorithms, which are scalable implementations of core machine learning algorithms that are optimized for SageMaker and GPU training. If you have your own algorithms built into SageMaker compatible Docker containers, you can train and host models using these as well. -
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bluetroller
A library and interface for controlling bluetooth LE devices
bluetroller is a library and interface for controlling all kinds of bluetooth LE devices. A vast number of devices can be controlled via Bluetooth LE, including fitness trackers, lighting, camera sliders, gimbals and many more. Right now these devices can only be controlled via phone apps which are frequently buggy, unmaintained and will stop working after some future phone update. This project aims to grow to become an exhaustive library of these devices. -
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Several language bindings for the FTDI D2XX driver used in FTDI's USB products. Currently supported languages are Python (pyd2xx), Java (jd2xx), CSharp (csd2xx) and LabVIEW (lvd2xx).
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Sparse Attention
"Generating Long Sequences with Sparse Transformers" examples
Sparse Attention is OpenAI’s code release for the Sparse Transformer model, introduced in the paper Generating Long Sequences with Sparse Transformers. It explores how modifying the self-attention mechanism with sparse patterns can reduce the quadratic scaling of standard transformers, making it possible to model much longer sequences efficiently. The repository provides implementations of sparse attention layers, training code, and evaluation scripts for benchmark datasets. It highlights... -
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Ansible Examples
A few starter examples of ansible playbooks, to show features
This repository collects practical, real-world examples of using Ansible to automate infrastructure, deployments, and configurations. Each directory demonstrates a specific use case—ranging from setting up web servers, load balancers, and databases to orchestrating multi-tier applications in cloud environments. The examples highlight common Ansible practices such as organizing inventories, writing reusable playbooks, using roles, and handling variables and templates. They’re designed to be...
