ML @ CMU

NOVEMBER 7, 2024

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.

Clustering 152

Clustering Cross Validation Machine Learning Machine Learning 152

Data Science Dojo

JULY 15, 2024

Technical Approaches: Several techniques can be used to assess row importance, each with its own advantages and limitations: Leave-One-Out (LOO) Cross-Validation: This method retrains the model leaving out each data point one at a time and observes the change in model performance (e.g., accuracy). shirt, pants). shirt, pants).

Machine Learning 307

Machine Learning Machine Learning Algorithm Clustering 307

Dataconomy

MARCH 17, 2025

By identifying patterns within the data, it helps organizations anticipate trends or events, making it a vital component of predictive analytics. Definition and overview of predictive modeling At its core, predictive modeling involves creating a model using historical data that can predict future events.

Decision Trees 91

Decision Trees Predictive Analytics Data Preparation Machine Learning 91

Data Science Dojo

AUGUST 19, 2024

This is used for tasks like clustering, dimensionality reduction, and anomaly detection. For example, clustering customers based on their purchase history to identify different customer segments. Networking Platforms: Meetup: Attend AI-related meetups and networking events to connect with professionals in the field.

AI 343

AI AI Machine Learning Machine Learning 343

Pickl AI

FEBRUARY 17, 2025

It uses predictive modelling to forecast future events and adaptiveness to improve with new data, plus generalization to analyse fresh data. The algorithm identifies patterns and structures within the data, such as clustering similar items or reducing dimensionality. spam detection) and regression tasks (e.g., predicting house prices).

Machine Learning 52

Machine Learning Machine Learning Supervised Learning ML 52

Pickl AI

OCTOBER 15, 2024

They identify patterns in existing data and use them to predict unknown events. Applications : Stock price prediction and financial forecasting Analysing sales trends over time Demand forecasting in supply chain management Clustering Models Clustering is an unsupervised learning technique used to group similar data points together.

Decision Trees 52

Decision Trees Hypothesis Testing Clustering Data Analysis 52

Pickl AI

AUGUST 9, 2024

Some of the most notable technologies include: Hadoop An open-source framework that allows for distributed storage and processing of large datasets across clusters of computers. Students should understand the concepts of event-driven architecture and stream processing. Knowledge of RESTful APIs and authentication methods is essential.

Big Data 52

Big Data Big Data Big Data Analytics Big Data Analytics 52