The easiest way to serve AI/ML models in production - Build Model Inference Service, LLM APIs, Multi-model Inference Graph/Pipelines, LLM/RAG apps, and more!
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Updated
Jun 10, 2024 - Python
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.
The easiest way to serve AI/ML models in production - Build Model Inference Service, LLM APIs, Multi-model Inference Graph/Pipelines, LLM/RAG apps, and more!
A unified SQL query interface and portable runtime to locally materialize, accelerate, and query datasets from any database, data warehouse, or data lake.
Web application for predicting the number of available bike stands at one of the MBajk bike stations.
A game theoretic approach to explain the output of any machine learning model.
Structured machine learning project
Core ML tools contain supporting tools for Core ML model conversion, editing, and validation.
Diabetes prediction utilizing established characteristics. The objective of this exercise is to showcase the efficacy of Machine learning. The dataset comprises various health-related attributes gathered to facilitate the creation of predictive models for detecting potential diabetes risks.
Tensors and Dynamic neural networks in Python with strong GPU acceleration
🤖 Collect practical AI repos, tools, websites, papers and tutorials on AI. 实用的AI百宝箱 💎
PyTorch/TorchScript/FX compiler for NVIDIA GPUs using TensorRT
Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
Scikit-learn compatible decision trees beyond those offered in scikit-learn
On-device AI across mobile, embedded and edge for PyTorch
Statistical Machine Intelligence & Learning Engine
🌎 🚙📚 Predicting travel times and traffic density on a highway in Slovenia
Automated discovery and classification of websites content through unsupervised learning approach
An ASL detection script utilizing a TensorFlow image classification model trained from scratch. It is tailored to recognize American Sign Language (ASL) alphabet letters from live video streams, and provides documentation covering the neural network architecture, installation, dataset details, training procedures, and real-time detection.
Evaluation and Tracking for LLM Experiments
[ICLR 2024] SemiReward: A General Reward Model for Semi-supervised Learning