Search Results for "python basic project" - Page 4
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Showing 170 open source projects for "python basic project"
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databooks
A CLI tool to reduce the friction between data scientists
databooks is a package to ease the collaboration between data scientists using Jupyter notebooks, by reducing the number of git conflicts between different notebooks and resolution of git conflicts when encountered. Simply specify the paths for notebook files to remove metadata. By doing so, we can already avoid many of the conflicts. Specify the paths for notebook files with conflicts to be fixed. Then, databooks finds the source notebooks that caused the conflicts and compares them (so no... -
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fastMRI
A large open dataset + tools to speed up MRI scans using ML
fastMRI is a large-scale collaborative research project by Facebook AI Research (FAIR) and NYU Langone Health that explores how deep learning can accelerate magnetic resonance imaging (MRI) acquisition without compromising image quality. By enabling reconstruction of high-fidelity MR images from significantly fewer measurements, fastMRI aims to make MRI scanning faster, cheaper, and more accessible in clinical settings. The repository provides an open-source PyTorch framework with data... -
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DeepMind Research
Implementations and code to accompany DeepMind publications
...The top level organizes many paper-specific directories across domains such as deep reinforcement learning, self-supervised vision, generative modeling, scientific ML, and program synthesis—for example BYOL, Perceiver/Perceiver IO, Enformer for genomics, MeshGraphNets for physics, RL Unplugged, Nowcasting for weather, and more. Each project folder typically includes its own README, scripts, and notebooks so you can run experiments or explore models in isolation, and many link to associated datasets or external environments like DeepMind Lab and StarCraft II. The codebase is primarily Jupyter Notebooks and Python, reflecting an emphasis on experimentation and pedagogy rather than production packaging. -
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Robin-Stocks API Library
This is a library to use with Robinhood Financial App
This is a library to use with Robinhood Financial App. It currently supports trading crypto-currencies, options, and stocks. In addition, it can be used to get real-time ticker information, assess the performance of your portfolio, and can also get tax documents, total dividends paid, and more. The code is simple to use, easy to understand, and easy to modify. With this library, you can view information on stocks, options, and cryptocurrencies in real-time, create your own robo-investor or... -
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DIG
A library for graph deep learning research
The key difference with current graph deep learning libraries, such as PyTorch Geometric (PyG) and Deep Graph Library (DGL), is that, while PyG and DGL support basic graph deep learning operations, DIG provides a unified testbed for higher level, research-oriented graph deep learning tasks, such as graph generation, self-supervised learning, explainability, 3D graphs, and graph out-of-distribution. If you are working or plan to work on research in graph deep learning, DIG enables you to... -
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Neural Network Visualization
Project for processing neural networks and rendering to gain insights
nn_vis is a minimalist visualization tool for neural networks written in Python using OpenGL and Pygame. It provides an interactive, graphical representation of how data flows through neural network layers, offering a unique educational experience for those new to deep learning or looking to explain it visually. By animating input, weights, activations, and outputs, the tool demystifies neural network operations and helps users intuitively grasp complex concepts. Its lightweight codebase is... -
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Data science blogs
A curated list of data science blogs
Data Science Blogs is a curated repository that aggregates a wide range of high-quality blogs and resources related to data science, machine learning, and analytics into a single organized collection. It serves as a discovery platform for practitioners, researchers, and learners who want to stay updated with industry trends, techniques, and insights without manually searching for reliable sources. The repository includes links to personal blogs, professional publications, and educational... -
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albert_zh
Implementation of A Lite Bert For Self-Supervised Learning Language
albert_zh is a Chinese ALBERT pretraining and model release repository. It implements ALBERT with TensorFlow and provides Chinese pretrained models designed to reduce parameter size while preserving strong language understanding performance. The project includes several model variants, such as tiny, small, base, large, and xlarge-style releases, giving users options for speed, size, and accuracy tradeoffs. It also provides guidance for fine-tuning downstream tasks such as sentence-pair... -
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Scripting Language Bindings
A port of WFOPT to the several scripting languages
This project contains bindings for various scripting languages to the Wheefun Options Parsing Library. It is meant to provide parity with the C implementation so .NET languages can take advantage of WFOPT. For more information, please see the main page. -
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Hacker Scripts
Based on a true story
...The README explains the origin story and highlights several canonical scripts and provides usage notes such as required environment variables and cron examples for scheduling. Contributors have provided implementations and ports in many languages and folders (shell, Ruby, Python, Node, Perl, PowerShell, Go, Java, etc.), and the project explicitly welcomes pull requests that add additional language implementations. -
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100+ Python Projects Challenge
100+ Python Projects Challenge
100+ Python Projects Challenge is a project-based Python learning repository focused on building many small applications and utilities. Instead of only practicing isolated syntax, it encourages learners to apply Python through complete mini-projects. The challenges span practical scripts, beginner applications, automation ideas, games, data tasks, and other hands-on exercises. -
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YOLOV4 Pytorch
This is a source code for YoloV4-pytorch that can be used to train you
YOLOV4 Pytorch is a PyTorch implementation of the YOLOv4 object detection model for training and running custom detection systems. The repository is structured around practical workflows, including training, prediction, evaluation, anchor generation, model configuration, and dataset annotation utilities. It supports VOC-style datasets and includes scripts for prediction, mAP evaluation, FPS testing, video prediction, batch prediction, and heatmap generation. The project added multi-GPU... -
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YOLOV3 Pytorch
This is a source code for yolo3-pytorch
YOLOV3 Pytorch is a PyTorch implementation of the YOLOv3 object detection model built for training, prediction, and evaluation. The repository provides a complete workflow for users who want to train their own object detector with VOC-style data or use pretrained weights. It includes utilities for annotation conversion, anchor generation, image prediction, video prediction, batch prediction, FPS measurement, heatmap output, and mAP evaluation. The project added multi-GPU training, target... -
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Official YOLOv7
YOLOv7: Trainable bag-of-freebies sets new state-of-the-art
YOLOv7 is the official implementation of the paper “YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors.” It is a PyTorch-based object detection project focused on high speed and strong accuracy for real-time computer vision. The repository provides model definitions, training scripts, testing tools, inference examples, pretrained weights, and deployment-oriented materials. YOLOv7 introduced training-time improvements that raise accuracy without... -
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Whisper Library
Whisper is a file-based time-series database format for Graphite
Whisper is one of three components within the Graphite project. Whisper is a fixed-size database, similar in design and purpose to RRD (round-robin-database). It provides fast, reliable storage of numeric data over time. Whisper allows for higher resolution (seconds per point) of recent data to degrade into lower resolutions for long-term retention of historical data. Copies data from src in dst, if missing. Unlike whisper-merge, don't overwrite data that's already present in the target... -
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Faster-Rcnn
This is a pytorch implementation library of faster-rcnn
Faster-Rcnn is a PyTorch implementation of the Faster R-CNN two-stage object detection model. It is designed for training and evaluating detectors on VOC-format datasets, including VOC07+12 and custom datasets arranged with VOC-style annotations and images. The repository includes scripts for training, prediction, evaluation, annotation generation, and model summary inspection. It supports backbone options through pretrained VGG and ResNet weights, making it useful for comparing feature... -
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DeepLabv3 Plus
Encoder-Decoder with Atrous Separable Convolution
DeepLabv3 Plus is a PyTorch implementation of DeepLabv3+ for semantic segmentation. It implements the encoder-decoder architecture with atrous separable convolution and provides a practical workflow for training, prediction, and mIoU evaluation. The repository supports VOC-style segmentation datasets and includes utilities for annotation generation, JSON dataset conversion, model summary inspection, prediction, and metric calculation. It provides pretrained weight workflows for MobileNetV2... -
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Unet
Source code for unet-pytorch, which can train its own model
Unet-pytorch is a PyTorch implementation of U-Net for semantic segmentation workflows. The repository is built around training, prediction, and mIoU evaluation for VOC-style segmentation data and medical-style datasets. It includes scripts for general training, medical dataset training, prediction, annotation handling, model summaries, and evaluation. The project supports multiple backbones, data processing utilities, extensive comments, and adjustable training parameters. Its README notes... -
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SageMaker Scikit-Learn Extension
A library of additional estimators and SageMaker tools based on scikit
A library of additional estimators and SageMaker tools based on scikit-learn. This project contains standalone scikit-learn estimators and additional tools to support SageMaker Autopilot. Many of the additional estimators are based on existing scikit-learn estimators. SageMaker Scikit-Learn Extension is a Python module for machine learning built on top of scikit-learn. In order to use the I/O functionalies in the sagemaker_sklearn_extension.externals module, you will also need to install the mlio version 0.7 package via conda. ... -
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SVoice (Speech Voice Separation)
We provide a PyTorch implementation of the paper Voice Separation
SVoice is a PyTorch-based implementation of Facebook Research’s study on speaker voice separation as described in the paper “Voice Separation with an Unknown Number of Multiple Speakers.” This project presents a deep learning framework capable of separating mixed audio sequences where several people speak simultaneously, without prior knowledge of how many speakers are present. The model employs gated neural networks with recurrent processing blocks that disentangle voices over multiple... -
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GDAL wheels for linux
GDAL wheels for python and C/C++ projects (Linux only)
To use precompiled wheels: 1) go to releases (Files) and download tarball needed; 2) install it with command: python3 -m pip install /path/to/wheel.whl Or simply use URL in pip: python3 -m pip install https://sourceforge.net/projects/gdal-wheels-for-linux/files/GDAL-3.1.4-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.whl/download URL may be found under "View details" button (i) To use GDAL in C/C++ project you need to link gdal lib AND all libs located at dir GDAL.libs (usually this folder resides inside python site-packages) To compile your own wheels see information given at forefather project: https://github.com/youngpm/gdalmanylinux Usually this is done via command `make wheels` GDAL wheels for Windows are provided by Christoph Gohlke at https://www.lfd.uci.edu/~gohlke/pythonlibs/#gdal Built with PROJ (proj.db is included), GEOS, EXPAT. ... -
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TensorFlow Examples
TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)
TensorFlow Examples is a comprehensive repository of example implementations, tutorials, and reference code intended to help newcomers and intermediate learners dive into TensorFlow quickly. It contains both Jupyter notebooks and raw source code, covering a broad range of tasks: from basic machine-learning and neural-network models to more advanced use cases, using both TensorFlow v1 and v2 APIs. For clarity and educational value, each example is accompanied by explanatory comments or... -
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YOLOR
implementation of paper - You Only Learn One Representation
YOLOR is the implementation of “You Only Learn One Representation,” a unified network approach for learning explicit and implicit knowledge together. The project focuses on object detection while exploring how a shared representation can support multiple tasks. It builds on the YOLO family and related PyTorch detection work, combining practical detector training with a research idea about unified representations. YOLOR includes model configurations, training code, evaluation scripts,... -
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pbxproj
A python module to manipulate XCode projects
This module can read, modify, and write a .pbxproj file from an Xcode 4+ project. 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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cnn-for-image-retrieval is a research-oriented project that demonstrates the use of convolutional neural networks (CNNs) for image retrieval tasks. The repository provides implementations of CNN-based methods to extract feature representations from images and use them for similarity-based retrieval. It focuses on applying deep learning techniques to improve upon traditional handcrafted descriptors by learning features directly from data. The code includes training and evaluation scripts that...
