Search Results for "python-gtksourceview2" - Page 79
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6596 projects for "python-gtksourceview2" with 1 filter applied:
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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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Go from Code to Production URL in SecondsSkip the Kubernetes configs. Cloud Run handles HTTPS, scaling, and infrastructure automatically. Two million requests free per month.
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Twint
An advanced Twitter scraping & OSINT tool written in Python
Twint is an advanced open-source Twitter scraping and OSINT tool written in Python that extracts tweets, user data, followers, likes, and more—without relying on Twitter’s API—making it highly useful for researchers, analysts, and hobbyists who want to bypass rate limits and access public Twitter data. -
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tkcalendar
Calendar widget for Tkinter
tkcalendar is a python module that provides the Calendar and DateEntry widgets for Tkinter. The DateEntry widget is similar to a Combobox, but the drop-down is not a list but a Calendar to select a date. tkcalendar is compatible with both Python 2 and Python 3. It support all locale settings supported by the system and the colors are customizable. -
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Deep-Learning-with-PyTorch-Tutorials
Deep Learning and PyTorch Introduction Video Tutorial with Source Code
Deep-Learning-with-PyTorch-Tutorials is a companion repository for an introductory deep learning course built around PyTorch. It provides source code, notebooks, and presentation materials for a practical video-based learning path. The lessons begin with PyTorch setup, tensors, indexing, mathematical operations, gradients, and basic optimization. They then move into neural networks, logistic regression, multilayer perceptrons, CNNs, ResNet, RNNs, LSTMs, autoencoders, VAEs, GANs, graph... -
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Machine Learning From Scratch
Bare bones NumPy implementations of machine learning models
ML-From-Scratch is an open-source machine learning project that demonstrates how to implement common machine learning algorithms using only basic Python and NumPy rather than relying on high-level frameworks. The goal of the project is to help learners understand how machine learning algorithms work internally by building them step by step from fundamental mathematical operations. The repository includes implementations of algorithms ranging from simple models such as linear regression and logistic regression to more complex techniques such as decision trees, support vector machines, clustering methods, and neural networks. ... -
$300 Free Credits for Your Google Cloud ProjectsLaunch your next project with $300 in free Google Cloud credits—no strings attached. Test, build, and deploy without risk. Use your credits across the entire Google Cloud platform to find what works best for your needs. After your credits are used, continue with always-free tier services. Only pay when you're ready to scale. Sign up in minutes and start exploring.
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PyTorch-BigGraph
Generate embeddings from large-scale graph-structured data
PyTorch-BigGraph (PBG) is a system for learning embeddings on massive graphs—think billions of nodes and edges—using partitioning and distributed training to keep memory and compute tractable. It shards entities into partitions and buckets edges so that each training pass only touches a small slice of parameters, which drastically reduces peak RAM and enables horizontal scaling across machines. PBG supports multi-relation graphs (knowledge graphs) with relation-specific scoring functions,... -
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Azure Machine Learning Python SDK
Python notebooks with ML and deep learning examples
Azure Machine Learning Python SDK is a curated repository of Python-based Jupyter notebooks that demonstrate how to develop, train, evaluate, and deploy machine learning and deep learning models using the Azure Machine Learning Python SDK. The content spans a wide range of real-world tasks — from foundational quickstarts that teach users how to configure an Azure ML workspace and connect to compute resources, to advanced tutorials on using pipelines, automated machine learning, and dataset handling. ... -
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Fav-up
Look up IP addresses using favicon hashes via Shodan
fav-up is an open source reconnaissance utility designed to identify servers and websites by analyzing favicon hashes and querying the Shodan search engine. It calculates the hash of a favicon image and then uses that value to search Shodan for other hosts that use the same icon. This technique is commonly used in security research and OSINT investigations to discover related infrastructure or services that may belong to the same organization. fav-up can retrieve favicon data from several... -
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Feather
Binary data frame storage for Python, R, and more
...It provides columnar serialization for data frames, making read and write operations faster than many text-based formats. The project was built to make sharing data across languages such as Python and R easier. Feather is powered by the Apache Arrow columnar memory specification, which helps it represent numeric, string, categorical, date, timestamp, boolean, and binary data efficiently. It also supports null and missing values across column types. Current development continues through Apache Arrow, with modern Python usage handled through pyarrow.feather. -
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Train ML Models With SQL You Already KnowBuild and deploy ML models using familiar SQL. Automate data prep with built-in Gemini. Query 1 TB and store 10 GB free monthly.
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distribution-is-all-you-need
The basic distribution probability Tutorial for Deep Learning Research
distribution-is-all-you-need is a Python-based probability tutorial aimed at deep learning researchers and students. It explains common discrete and continuous distributions through short scripts, formulas, descriptions, and plotted graphs. Covered topics include uniform, Bernoulli, binomial, categorical, multinomial, beta, Dirichlet, gamma, exponential, Gaussian, normal, chi-squared, and Student's t distributions. -
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TF Quant Finance
High-performance TensorFlow library for quantitative finance
TF Quant Finance is a high-performance library of quantitative finance components built on TensorFlow, aimed at research and production workloads. It implements pricing engines, risk measures, stochastic models, optimizers, and random number generators that are differentiable and vectorized for accelerators. Users can value options and fixed-income instruments, simulate paths, fit curves, and calibrate models while leveraging TensorFlow’s jit compilation and automatic differentiation. The... -
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Resemblyzer
A python package to analyze and compare voices with deep learning
...It can help identify whether two recordings sound like the same speaker or visualize voice relationships across many samples. Its main value is making speaker representation accessible through a simple Python workflow. -
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AES Everywhere
Cross Language AES 256 Encryption Library
AES Everywhere is Cross Language Encryption Library that provides the ability to encrypt and decrypt data using a single algorithm in different programming languages and on different platforms. This is an implementation of the AES algorithm, specifically CBC mode, with 256-bit key length and PKCS7 padding. It implements OpenSSL-compatible cryptography with randomly generated salt. -
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SimpleITK: a simplified layer build on top of the Insight Toolkit (ITK), intended to facilitate its use in rapid prototyping, education and interpreted languages.
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ELI5
A library for debugging/inspecting machine learning classifiers
ELI5 is a Python library designed to help developers interpret, debug, and explain the predictions of machine learning models. The project focuses on improving model transparency by providing tools that visualize feature importance and prediction reasoning. It supports several popular machine learning frameworks including scikit-learn, XGBoost, LightGBM, CatBoost, and Keras. -
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CCZero (中国象棋Zero)
Implement AlphaZero/AlphaGo Zero methods on Chinese chess
ChineseChess-AlphaZero is a project that implements the AlphaZero algorithm for the game of Chinese Chess (Xiangqi). It adapts DeepMind’s AlphaZero method—combining neural networks and Monte Carlo Tree Search (MCTS)—to learn and play Chinese Chess without prior human data. The system includes self-play, training, and evaluation pipelines tailored to Xiangqi's unique game mechanics. -
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Activity Recognition
Resources about activity recognition
...It is not a single integrated software package but rather a knowledge base organizing feature extraction methods, deep learning approaches, transfer learning strategies, datasets, and representative research in behavior recognition. The repository includes links to code in MATLAB, Python, summaries of algorithms, datasets, and relevant research papers. Feature extraction method summaries (e.g. motion, sensor, vision). Deep learning for activity recognition references. -
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Buster
OSINT tool for discovering information linked to email addresses
Buster is an open source OSINT tool designed for email reconnaissance and information gathering. It helps investigators, security researchers, and penetration testers discover publicly available information related to email addresses and usernames. It can analyze an email address to identify associated social media accounts, references across the web, and potential data breaches linked to that email. It also performs reverse WHOIS lookups to discover domains that may have been registered... -
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Olex2 is visualisation software for small-molecule crystallography developed at Durham University/EPSRC. It provides comprehensive tools for crystallographic model manipulation for the end user and an extensible development framework for programmers. The project has been supported by Olexsys Ltd since 2010.
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AIAlpha
Use unsupervised and supervised learning to predict stocks
AIAlpha is a machine learning project focused on building predictive models for financial markets and algorithmic trading strategies. The repository explores how artificial intelligence techniques can analyze historical financial data and generate predictions about asset price movements. It provides a research-oriented environment where users can experiment with data processing pipelines, model training workflows, and quantitative trading strategies. The project typically involves collecting... -
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GIF for CLI
Takes in a GIF, short video, or a query to the Tenor GIF API
gif-for-cli is a small, playful utility that brings animated GIFs to the command line by rendering frames directly in a terminal. It takes an input GIF (or a URL) and converts each frame into a terminal-friendly representation, timing updates to approximate the original animation. Depending on terminal capabilities, it can use ANSI color blocks or image protocols to achieve surprisingly faithful playback. The tool includes conveniences such as looping control, scaling to fit your terminal,... -
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Software for exploring & solving polyform puzzles, written in Python. Includes solvers for: pentominoes/polyominoes, solid pentominoes, Soma cubes, polycubes, polyiamonds, polyhexes, polysticks, and more to come.
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A symbolic framework for C++, Python and Octave implementing automatic differentiation by source code transformation in forward and reverse modes on sparse matrix-valued computational graphs.
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TestLink-API-Python-client
Python XML-RPC client for TestLink
TestLink-API-Python-client is a Python XML-RPC client for TestLink Initially based on James Stock testlink-api-python-client R7 and Olivier Renault JinFeng idea - an interaction of TestLink, Robot Framework and Jenkins. TestLink-API-Python-client delivers two main classes - TestlinkAPIGeneric - Implements the Testlink API methods as generic PY methods with error handling - TestlinkAPIClient - Inherits from TestlinkAPIGeneric and defines service methods like "copyTCnewVersion" and the helper class - TestLinkHelper - search connection parameter from environment variables and command line arguments -
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pybag
Crossplatform files synchronization and backup portable tool.
PYBAG implements a portable bag and is intended for fast synchronization and backup. It lets you use a portable digital storage device to carry your electronic documents similar to the way you can use a bag to carry paper documents. You can synchronize the bag with your original files easily. If a synchronization conflict occurs, it will be reported. You can specify rules for automatic conflict resolution. With PYBAG, you can backup files and synchronize any changes made to the...