Popular GitHub Repositories for Dbscan Clusters

TensorFlowOnSpark brings TensorFlow programs to Apache Spark clusters.

Simple, scalable AI model deployment on GPU clusters

prima.cpp: Speeding up 70B-scale LLM inference on low-resource everyday home clusters

The first machine learning framework that encourages learning ML concepts instead of memorizing class functions.

Enhances construction site safety using YOLO for object detection, identifying hazards like workers without helmets or safety vests, and proximity to machinery or vehicles. HDBSCAN clusters safety cone coordinates to create monitored zones. Post-processing algorithms improve detection accuracy.

A repository contains more than 12 common statistical machine learning algorithm implementations. 常见10余种机器学习算法原理与实现及视频讲解。@月来客栈 出品

An open-source toolkit for deploying and managing high performance clusters for HPC, AI, and data analytics workloads.

BERT, AWS RDS, AWS Forecast, EMR Spark Cluster, Hive, Serverless, Google Assistant + Raspberry Pi, Infrared, Google Cloud Platform Natural Language, Anomaly detection, Tensorflow, Mathematics

由时间空间成对组成的轨迹序列，通过循环神经网络lstm，自编码器auto-encode，时空密度聚类st-dbscan做异常检测

Efficient LLM inference on Slurm clusters using vLLM.

A catkin workspace in ROS which uses DBSCAN to identify which points in a point cloud belong to the same object.

Create, List, Update, Delete Amazon EKS clusters. Deploy and manage software on EKS. Run distributed model training and inference examples.

Topic modelling on financial news with Natural Language Processing

dask-pytorch-ddp is a Python package that makes it easy to train PyTorch models on dask clusters using distributed data parallel.

This clustering based anomaly detection project implements unsupervised clustering algorithms on the NSL-KDD and IDS 2017 datasets

Inference in Bayesian Belief Networks using Probability Propagation in Trees of Clusters (PPTC) and Gibbs sampling

This repository aims to showcase how to finetune a FM model in Amazon EKS cluster using, JupyterHub to provision notebooks and craft both serving and training scripts, RayOperator to manage Ray Clusters and Karpenter to manage Node Scaling.

An application using Machine Learning to automatically create clusters of queries from Google Search Console.

An interactive approach to understanding Machine Learning using scikit-learn

Implementation of feature engineering from Feature engineering strategies for credit card fraud