machine-learning
Machine learning is the practice of teaching a computer to learn. The concept uses pattern recognition, as well as other forms of predictive algorithms, to make judgments on incoming data. This field is closely related to artificial intelligence and computational statistics.
Repositories (1432)
Keras Temporal Convolutional Network. Supports Python and R.
A Deep Learning Approach for Password Guessing (https://arxiv.org/abs/1709.00440)
Elyra extends JupyterLab with an AI centric approach.
Build LLM-powered applications in Ruby
The Virtual Feature Store. Turn your existing data infrastructure into a feature store.
A community-driven collection of RAG (Retrieval-Augmented Generation) frameworks, projects, and resources. Contribute and explore the evolving RAG eco...
CVNets: A library for training computer vision networks
[ICLR 2024] Official implementation of "TimeMixer: Decomposable Multiscale Mixing for Time Series Forecasting"
A lightweight 3D Morphable Face Model library in modern C++
Easy Machine Learning is a general-purpose dataflow-based system for easing the process of applying machine learning algorithms to real world tasks.
PyTorch implementation of convolutional neural networks-based text-to-speech synthesis models
This is the code for Deformable Neural Radiance Fields, a.k.a. Nerfies.
Physical Symbolic Optimization
Web labeling tool for bitmap images and point clouds
Using python and scikit-learn to make stock predictions
spark ml 算法原理剖析以及具体的源码实现分析
🚀 FREE AI Resources - 🎓 Courses, 👷 Jobs, 📝 Blogs, 🔬 AI Research, and many more - for everyone!
Use unsupervised and supervised learning to predict stocks
Training PyTorch models with differential privacy
Official front-end implementation of ComfyUI
Implementation of "BitNet: Scaling 1-bit Transformers for Large Language Models" in pytorch
Feathr – A scalable, unified data and AI engineering platform for enterprise
A Julia machine learning framework
SLING - A natural language frame semantics parser
TinyML AI inference library
Deep learning in Rust, with shape checked tensors and neural networks
Notebooks about Bayesian methods for machine learning
Gaussian processes in TensorFlow
BERT score for text generation
The AI Datastore for Schemas, BLOBs, and Predictions. Use with your apps or integrate built-in Human Supervision, Data Workflow, and UI Catalog to get...
A timeline of the latest AI models for audio generation, starting in 2023!
Ergonomic machine learning for everyone.
fastdup is a powerful, free tool designed to rapidly generate valuable insights from image and video datasets. It helps enhance the quality of both im...
Automatically Visualize any dataset, any size with a single line of code. Created by Ram Seshadri. Collaborators Welcome. Permission Granted upon Req...
💫 Models for the spaCy Natural Language Processing (NLP) library
A minimal benchmark for scalability, speed and accuracy of commonly used open source implementations (R packages, Python scikit-learn, H2O, xgboost, S...
TensorFlow binaries supporting AVX, FMA, SSE
Generate pages from any sketch or images.
A curated list of awesome Speaker Diarization papers, libraries, datasets, and other resources.
An unofficial C#/.NET SDK for accessing the OpenAI GPT-3 API
Petastorm library enables single machine or distributed training and evaluation of deep learning models from datasets in Apache Parquet format. It sup...
Natural Gradient Boosting for Probabilistic Prediction
A curated list of Graph/Transformer-based fraud, anomaly, and outlier detection papers & resources
A package for the sparse identification of nonlinear dynamical systems from data
The Self-Coding System for Your App — Alan AI SDK for iOS
A Python package for time series classification
TensorFlow template application for deep learning
Genetic Programming in Python, with a scikit-learn inspired API
Find big moving stocks before they move using machine learning and anomaly detection
Provide an input CSV and a target field to predict, generate a model + code to run it.