Search Results for "python-i2c-tiny-usb" - Page 90
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10319 projects for "python-i2c-tiny-usb" with 1 filter applied:
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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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QMForge reads output from various quantum mechanical calculations and provides tools for analyzing these results. Specifically, population (Mulliken and C-squared), fragment, and charge decomposition analyses are available. See https://qmforge.net for more info.
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StarsAndClown
Github Star Gathering Treatment List
StarsAndClown is a repository by the same maintainer that seems intended as a lighthearted “ranking / listing” project, possibly gathering interesting or amusing GitHub repositories, trending topics, or community “stars” — perhaps with a humorous or satirical twist given the name. The concept suggests a curated (or semi-automated) list of GitHub repos worth noting: whether because of popularity, novelty, or community interest — giving “people who eat grapes” (i.e. spectators) a way to enjoy... -
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Scikit-learn Tutorial
An introductory tutorial for scikit-learn
...Although the GitHub repository has been archived and is read-only, it is still a valuable snapshot of early, hands-on teaching material for scikit-learn and machine learning in Python. -
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Image Quality Assessment
Convolutional Neural Networks to predict aesthetic quality of images
Image Quality Assessment is an open-source deep learning project that implements neural models for predicting the aesthetic and technical quality of digital images. The repository provides an implementation inspired by the NIMA (Neural Image Assessment) research approach, which uses convolutional neural networks trained on human-annotated datasets to estimate image quality scores. The goal of the project is to automatically evaluate images based on perceived quality factors such as... -
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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12306 Ticket Buying Assistant
12306 Smart ticket swiping, ticket booking
12306 is an automation and ticket-purchasing tool designed to interact with China’s official railway booking system, providing users with a programmatic way to search, reserve, and purchase train tickets. The project replicates the workflow of the official platform while adding automation features that help users secure tickets in high-demand scenarios. It supports querying schedules, checking seat availability, and performing booking actions through scripts, which reduces the need for... -
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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. ... -
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pysourceinfo
RTTI for Python Source and Binary Files
The 'pysourceinfo' package provides source information on Python runtime objects based on 'inspect', 'sys', 'os', and 'imp'. The covered objects include packages, modules, functions, methods, scripts, and classes by two views: - File System View - packages, modules, and linenumbers - based on files and paths - Runtime Object View - callables, classes, and containers - based on in-memory RTTI / introspection The supported platforms are: - Linux, BSD, Unix, OS-X, Cygwin, and Windows - Python2, Python3 - CPython, PyPy Object addresses within modules - Object Identifier OID - and the display of the runtime call flow are supported by 'PyStackInfo'. ... -
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Native File Dialog
Neat C library that portably invokes native file open and save dialogs
A tiny, neat C library that portably invokes native file open, folder select, and save dialogs. Write dialog code once and have it pop up native dialogs on all supported platforms. Avoid linking large dependencies like wxWidgets and qt. Tested, works alongside libsdl on all platforms, for the game developers out there. -
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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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pythonids
Enumeration of Python implementations and releases
The ‘pythonids‘ package provides the enumeration of Python syntaxes and the categorization of Python implementations. This enables the development of fast and easy portable generic code for arbitrary platforms in IT and IoT landscapes consisting of heterogeneous physical and virtual runtime environments. The current supported syntaxes are Python2.7+ and Python3 for the Python implementations: CPython IPython (based on CPython) IronPython Jython PyPy -
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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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pyPIDTuneMethods
PID controller design and tuning
pyPIDTuneMethods is a free python-based tool for PID controller design and tuning. pyPIDTuneMethods is based on scipy (numpy, scipy) <http://www.scipy.org/ >, guiqwt <http://code.google.com/p/guiqwt/ >, python control <http://python-control.org/> and pyQt5 <http://www.riverbankcomputing.co.uk >. If you are not familiar with python you can use winpython <http://winpython.sourceforge.net/>. -
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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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setupjavax
Provides Java and integrated Jython/Pyhon + Java builds
The ‘setupjavax‘ package provides extension modules for the build of Java and Jython packages. The current release supports the following commands, additional are coming soon: - build_java - Java build and packaging for Python. Supports Java packaging for Python projects, adds native Java modules for Jython. - build_jy - Integrated Python and Java builds for Jython. Supports combined Java and Python / Jython packaging. Calls build_py and build_java. -
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yz-next-apyref
Arno-Can's Python based API Reference Generator.
Multi-Syntax-Version and Multi-Implementation API reference documentation generator. Supports local and remote sources. -
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yapydata
Lower-Layer unified data - JSON, XML, YAML + INI, CFG, properties
The yapydata - Yet Another Python Data - provides a unified interface for the access to various data syntaxes. Therefore it encapsulates the libraries by offering a common API with the canonical internal data as JSON compatible Python in-memory structure. The application is foreseen in particular for the lower layer of the software stack including setup-tools. -
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setupdocx
Multidocument automation by templates - for sphinx, mkdocs, epydoc ...
The ‘setupdocx‘ provides a control layer for continuous documentation by the simplified creation, packaging, and installation of documentation. The provided commands are distributed as entry points and optional base classes for further customization into 'setup.py' - setuptools / distutils. Manages arbitrary document templates for the supported builder, supports multiple builds with arbitrary document layouts, designs, and patched contents. The current release supports the following... -
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yapyutils
Utilities for platform indepentent low-level system APIs.
The 'yapyutils' - Yet Another Python Utils - package provides miscellaneous *Python* utilities for the adaptation of platform independent APIs of the low-level part of the software stack. These are e.g. used for extensions of the *setuptools* and *distutils*, thus reduce the package dependency and avoid circular dependencies whenever possible by using standard packages and classes only. -
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setuplib
Extensions for setuptools - detailed information on entry points
The *setuplib* package provides core functions for the query of meta information and installation repositories of *Python* packages. It provides query and filter options on the installed packages and the available information, while displaying the result data in various formats, e.g. as table, list, or JSON, XML, YAML, CSV, etc. The provided commands and extension points integrate seamless into the standard *setuptools* and/or *distutils*. The *setuplib* is member of the group *setuplib* of extension components for the common *setup.py* installer. ... -
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setuptestx
Support of unit tests on multiple platforms and implementations.
The 'setuptestx' supports a common call interface for the major implementations and releases of Python on various operating systems and their variants of distributions. The current provided implementations are: - CPython, IPython, PyPY : Python2.7, and Python3.5+ - IronPython, Jython : Python2.7 For the OS see *Tested Platforms* in the manuals. -
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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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