Search Results for "source" - Page 9
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367 projects for "source" with 2 filters applied:
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Weld
High-performance runtime for data analytics applications
Weld is a programming language and runtime designed to improve the performance of data-intensive applications by optimizing computations across multiple libraries. Instead of optimizing individual functions independently, Weld introduces an intermediate representation that allows different frameworks to share optimization opportunities. This approach reduces data movement between libraries and enables the system to generate highly optimized machine code for parallel execution. Weld is... -
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Top deep learning Github repositories
Top 200 deep learning Github repositories sorted by stars
...The repository categorizes projects related to neural networks, computer vision, natural language processing, reinforcement learning, and other areas of artificial intelligence. By collecting popular open-source implementations in one place, the project simplifies the process of exploring cutting-edge tools and research implementations for deep learning practitioners. The curated lists are particularly helpful for developers who want to quickly identify well-maintained projects with strong community support. -
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Literature of Deep Learning for Graphs
A comprehensive collection of recent papers on graph deep learning
Literature of Deep Learning for Graphs is a curated repository that collects research papers and educational resources related to deep learning methods for graph-structured data. The project organizes important academic work covering topics such as graph neural networks, graph embeddings, knowledge graphs, and network representation learning. By structuring the literature into categories, the repository allows researchers to quickly identify influential papers in specific subfields of graph... -
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TensorFlow Machine Learning Cookbook
Code for Tensorflow Machine Learning Cookbook
TensorFlow Machine Learning Cookbook repository provides practical code examples and educational materials that accompany the book TensorFlow Machine Learning Cookbook. The repository contains numerous Python scripts and Jupyter notebooks that demonstrate how to implement machine learning algorithms and neural networks using the TensorFlow framework. Each section focuses on a different aspect of machine learning development, including tensor manipulation, model training, optimization... -
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Machine Learning with TensorFlow
Accompanying source code for Machine Learning with TensorFlow
Machine Learning with TensorFlow is an open repository containing the source code and practical examples that accompany the book Machine Learning with TensorFlow. The project provides numerous code samples demonstrating how to build machine learning models using the TensorFlow framework. These examples illustrate core machine learning concepts such as regression, classification, clustering, and neural networks through practical implementations. -
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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. -
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AI Cheatsheets
Essential Cheat Sheets for deep learning and machine learning research
cheatsheets-ai is an open-source repository that collects essential cheat sheets covering many tools and concepts used in machine learning, deep learning, and data science. The project aims to provide quick-reference materials that help engineers, researchers, and students review key techniques and frameworks without reading extensive documentation. It compiles cheat sheets for widely used libraries and technologies such as TensorFlow, Keras, NumPy, Pandas, Scikit-learn, Matplotlib, and PySpark. ... -
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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. -
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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... -
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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. The library allows users to inspect model weights, analyze decision trees, and compute permutation feature importance... -
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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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spark-ml-source-analysis
Spark ml algorithm principle analysis and specific source code
spark-ml-source-analysis is a technical repository that analyzes the internal implementation of machine learning algorithms within Apache Spark’s MLlib library. The project aims to help developers and data scientists understand how distributed machine learning algorithms are implemented and optimized inside the Spark ecosystem. Instead of providing a runnable software system, the repository focuses on explaining algorithm principles and examining the underlying source code used in Spark’s machine learning package. ... -
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Machine Learning Mindmap
A mindmap summarising Machine Learning concepts
Machine Learning Mindmap repository is an open educational project that presents a comprehensive visual overview of the machine learning ecosystem through a structured mind map and cheat sheet. The project organizes a wide range of machine learning topics into an interconnected diagram that helps learners understand how concepts relate to one another across the broader field of artificial intelligence. The mind map covers fundamental areas such as data preprocessing, statistical analysis,... -
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TensorFlow Docs
TensorFlow latest official documentation Chinese version
...The repository contains translated guides, API explanations, tutorials, and conceptual documentation that mirror the structure of the original TensorFlow documentation site. Contributors from technology companies, universities, and the open-source community collaborate to maintain and update the translations so they stay aligned with new TensorFlow releases. The documentation covers fundamental concepts such as tensors, computational graphs, model training, optimization, and neural network APIs, along with advanced topics including distributed training and production deployment. -
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Papers with Code
List of different papers for coding
pwc is an open-source repository that compiles machine learning and artificial intelligence research papers together with their corresponding implementation code. The project functions as a curated dataset linking academic publications with practical software implementations, allowing researchers and engineers to quickly locate code that reproduces published results. -
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SSD
A PyTorch Implementation of Single Shot MultiBox Detector
SSD is a PyTorch implementation of the Single Shot MultiBox Detector, a well-known object detection architecture introduced in the original SSD paper. It is built to help users train, evaluate, and experiment with object detection models using PyTorch rather than the original Caffe implementation. The repository includes the major components needed for an object detection workflow, including training scripts, evaluation scripts, demos, and utility modules. It supports commonly used benchmark... -
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DS-Take-Home
Solution to the book A Collection of Data Science Take-Home Challenge
DS-Take-Home is a repository that provides practical solutions to a series of real-world data science challenges inspired by the book A Collection of Data Science Take-Home Challenges. The project is designed as a learning resource where aspiring data scientists can study how typical industry-style take-home assignments are solved using data analysis and machine learning techniques. Each challenge is implemented in a separate Jupyter notebook that walks through the process of analyzing... -
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LibrePhotos
A self-hosted open source photo management service
LibrePhotos is an open-source self-hosted photo management platform designed to organize, browse, and analyze personal media libraries while preserving user privacy. The system allows individuals to store and manage their photos and videos locally rather than relying on commercial cloud services. It provides features similar to services like Google Photos but runs on a private server controlled by the user. -
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MIT Deep Learning
Tutorials, assignments, and competitions for MIT Deep Learning
MIT Deep Learning is an open-source repository that contains tutorials, assignments, and learning materials related to deep learning courses taught at MIT. The repository provides hands-on tutorials that introduce the fundamental concepts behind neural networks, deep learning architectures, and modern machine learning techniques. Many of the tutorials include practical implementations that demonstrate tasks such as image classification, generative models, and neural network training workflows. ... -
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DeepTraffic
DeepTraffic is a deep reinforcement learning competition
DeepTraffic is a deep reinforcement learning simulation designed to teach and evaluate autonomous driving algorithms in a dense highway environment. The system presents a simulated multi-lane highway where an AI-controlled vehicle must navigate traffic while maximizing speed and avoiding collisions. Participants design neural network policies that determine the vehicle’s actions, such as accelerating, decelerating, changing lanes, or maintaining speed. The project was created as part of an... -
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LUMINOTH
Deep Learning toolkit for Computer Vision
LUMINOTH is an open-source deep learning toolkit designed for computer vision tasks, particularly object detection. The framework is implemented in Python and built on top of TensorFlow and the Sonnet neural network library, providing a modular environment for training and deploying detection models. It was created to simplify the process of building and experimenting with deep learning models capable of identifying objects within images. -
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Machine learning Resources
Some learning materials and research introduction on machine learning
...The repository organizes materials that cover topics such as classification algorithms, neural networks, feature engineering, and model evaluation. Many sections reference research papers, tutorials, and open-source implementations that allow users to explore specific machine learning methods in greater depth. The project is maintained by researcher Jindong Wang, whose work focuses on machine learning research areas including transfer learning, domain adaptation, and robust learning methods. -
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BossSensor
Hide screen when boss is approaching
BossSensor is an experimental open-source application that uses computer vision and machine learning to detect when a specific person, such as a supervisor or manager, approaches a computer workstation. The project uses a webcam to continuously capture images and analyze them using a face classification model trained to distinguish between the designated “boss” and other individuals. -
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Lihang
Statistical learning methods (2nd edition) [Li Hang]
Lihang is an open-source repository that provides educational notes, mathematical derivations, and code implementations based on the book Statistical Learning Methods by Li Hang. The repository aims to help readers understand the theoretical foundations of machine learning algorithms through practical implementations and detailed explanations. It includes notebooks and scripts that demonstrate how key algorithms such as perceptrons, decision trees, logistic regression, support vector machines, and hidden Markov models work in practice. ... -
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The GAN Zoo
A list of all named GANs
The GAN Zoo is an open-source repository that compiles a comprehensive list of Generative Adversarial Network models published in research literature. The project began as a community effort to track the rapidly growing number of GAN architectures appearing in machine learning papers. Because new GAN models are frequently introduced in research publications, the repository serves as a convenient catalog that organizes them in one location.
