Machine Learning
Showing 36 of 1845 projects
A collection of transformer protein language models for predicting structure, function, and designing proteins from sequences.
Course materials for the Johns Hopkins Data Science Specialization on Coursera.
Course materials for the Johns Hopkins Data Science Specialization on Coursera.
A state-of-the-art Natural Language Processing library built on Apache Spark, offering 100,000+ pretrained models and pipelines in 200+ languages.
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Original implementation and hyperparameters for the 2014 paper "Generative Adversarial Networks" (GANs).
A fast parallel implementation of the Connectionist Temporal Classification (CTC) loss function for CPU and GPU.
A curated list of practical resources for responsible machine learning, covering interpretability, governance, safety, and ethics.
An open-source solution for continuous validation of machine learning models and data, from research to production.
An open-source cross-platform performance library of basic building blocks for deep learning applications, optimized for CPUs and GPUs.
A research framework for reinforcement learning providing modular building blocks and reference agent implementations.
A Unity-based simulator for training self-driving car models using deep learning.
Snips Python library to extract meaning from text
An open-source threat hunting platform with advanced analytics capabilities built on ELK stack, Apache Spark, and Jupyter notebooks.
A curated list of satellite and aerial imagery datasets with annotations for computer vision and deep learning tasks.
A highly efficient, scalable Gaussian process library implemented in PyTorch with GPU acceleration and modular design.
A curated collection of high-quality resources for quantitative and algorithmic trading with a focus on machine learning applications.
A browser-based tool that lets anyone create machine learning models without writing code, using TensorFlow.js.
A MATLAB/Octave toolbox for deep learning with implementations of neural networks, deep belief nets, autoencoders, and convolutional networks.
A curated list of open-source tools for professional robotic development in C++ and Python, covering ROS, autonomous driving, and aerospace.
Intel's reference deep learning framework designed for high performance across CPUs, GPUs, and custom hardware.
Enables distributed TensorFlow training and inferencing on Apache Spark and Hadoop clusters with minimal code changes.
A curated list of 100 foundational and influential papers in natural language processing for students and researchers.
Fast Python library for collaborative filtering recommendation algorithms on implicit feedback datasets.
A collection of Jupyter notebooks accompanying a 10-part video series teaching machine learning with Python's scikit-learn library.
A Python library for self-supervised learning on images, providing a modular PyTorch-like framework with support for modern SSL models.
An open-source, locally-runnable code completion engine using large language models that works on CPU.
A collection of handwritten notes, notebooks, and resources for Andrew Ng's Deep Learning Specialization on Coursera.
A Java dataframe and visualization library for data loading, cleaning, transformation, and analysis.
A C#/.NET library for efficient local inference of LLaMA and other large language models, based on llama.cpp.
R code examples from the 'Machine Learning for Hackers' book, demonstrating practical machine learning techniques.
An open-source platform for building, training, and monitoring large-scale deep learning applications with full lifecycle MLOps.
An end-to-end platform for applied reinforcement learning and contextual bandits, originally developed at Facebook for production recommendation systems.
A procedural Blender pipeline for generating photorealistic training images for computer vision and machine learning.
A tiny and efficient C++/Python binding library with faster compilation, smaller binaries, and lower runtime overhead than pybind11.
The fastest way to build data pipelines with iterative development and deployment anywhere.
A TensorFlow project template with a well-designed folder structure and OOP design to accelerate deep learning development.
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