article thumbnail

Identification of Hazardous Areas for Priority Landmine Clearance: AI for Humanitarian Mine Action

ML @ CMU

In close collaboration with the UN and local NGOs, we co-develop an interpretable predictive tool for landmine contamination to identify hazardous clusters under geographic and budget constraints, experimentally reducing false alarms and clearance time by half. The major components of RELand are illustrated in Fig.

article thumbnail

Hierarchical Clustering in Machine Learning: An In-Depth Guide

Pickl AI

Summary: Hierarchical clustering in machine learning organizes data into nested clusters without predefining cluster numbers. Unlike partition-based methods such as K-means, hierarchical clustering builds a nested tree-like structure called a dendrogram that reveals the multi-level relationships between data points.

professionals

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

PEFT fine tuning of Llama 3 on SageMaker HyperPod with AWS Trainium

AWS Machine Learning Blog

The process of setting up and configuring a distributed training environment can be complex, requiring expertise in server management, cluster configuration, networking and distributed computing. Scheduler : SLURM is used as the job scheduler for the cluster. You can also customize your distributed training.

AWS 106
article thumbnail

Text mining

Dataconomy

Clustering: Grouping similar data points to identify patterns. Key techniques in text mining Text mining has significantly advanced with the introduction of deep learning. This development allows for more nuanced and sophisticated analyses as neural networks iteratively learn from vast datasets.

article thumbnail

Map Earth’s vegetation in under 20 minutes with Amazon SageMaker

AWS Machine Learning Blog

Although setting up a processing cluster is an alternative, it introduces its own set of complexities, from data distribution to infrastructure management. We use the purpose-built geospatial container with SageMaker Processing jobs for a simplified, managed experience to create and run a cluster. format("/".join(tile_prefix),

ML 119
article thumbnail

Machine Learning Algorithms Explained with Real-World Use Cases

How to Learn Machine Learning

Unsupervised Learning Algorithms Unsupervised learning covers all and any learning procedures in which the data has no labels or targets: you want to discover some hidden structure or pattern in that data. Hence you will have clustering and dimensionality reduction as the main two kinds of unsupervised learning.

article thumbnail

Classics Never Fade Away: Decipher Gaussian Mixture Model and Its Variants!

Towards AI

Figure 1: Gaussian mixture model illustration [Image by AI] Introduction In a time where deep learning (DL) and transformers steal the spotlight, its easy to forget about classic algorithms like K-means, DBSCAN, and GMM. Consider the everyday clustering puzzles: customer segmentation, social network analysis, or image segmentation.