Mediaspace scheduled maintenance: Aug 25, 2026 07:00 - 12:00 AM. During this time, videos will be temporarily unavailable. Check status updates.

Concept

Data mining

Related lectures (32)

Data Issues in Research

Explores challenges in data assumptions, biases, and more in research, including incomplete write-ups and frustrations of newcomers.

Introduction to Spark runtime architecture

Introduces Apache Spark, covering its key features, history, RDDs, architecture, and distributed computing framework.

Graph Mining: Social Networks and Data Analysis

Explores graph mining in social networks, covering data analysis and community detection.

Big Data Best Practices and Guidelines

Covers best practices and guidelines for big data, including data lakes, architecture, challenges, and technologies like Hadoop and Hive.

Association Rules: Frequent Itemsets

Explores Association Rule Mining, emphasizing Frequent Itemsets and Alternative Measures of Interest, including the FP-Growth algorithm and performance comparison.

Data Analysis: KMnO4 Concentrations

Covers the analysis of KMnO4 concentrations using data from a CSV file.

Apprenticeship in Venice: Garzoni Project

Delves into the apprenticeship system in Venice between the 16th and 18th centuries, focusing on the 'garzoni'.

Excel Upgrade: Advanced Functions and Data Analysis

Covers advanced Excel functions and data analysis techniques, including automatic recording and using Solver.

Biomechanics: Velocity Analysis

Explores the analysis of velocity data in biomechanics using Excel for visualization and interpretation.

Real-time Data Analysis

Explores real-time data analysis, challenges of rapid data growth, estimation problems, and event timeline reconstruction.

Association Rules

Explores Association Rule Mining, including support, confidence, single- and multi-dimensional rules, and the Apriori algorithm.

Introduction to Data Stream Processing

Covers the fundamentals of data stream processing, including tools like Apache Storm and Kafka, key concepts like event time and window operations, and the challenges of stream processing.

Atomistic Machine Learning: Physics and Data

Explores Atomistic Machine Learning, integrating physical principles into models to predict molecular properties accurately.

When to Use Machine Learning MOOC: IoT Systems and Industrial Applications with Design Thinking

Explains the conditions for using machine learning in complex problems with patterns in data and access to a dataset.

Text Mining and Data Curation MOOC: Neuroscience Reconstructed: Genetics and Brain Development

Explores text mining, data curation, and brain connectivity in neuroscience.

Distributed Information Systems: Course Overview

Introduces the Distributed Information Systems course, emphasizing key concepts and practical tools for data processing.

Data Analysis: Car Dataset

Focuses on analyzing a car dataset, extracting key information, and printing car details.

Decision Tree Classification Log in to Mediaspace to watch this video

Covers decision tree classification using KNIME Analytics Platform for data preprocessing and model creation.

Data Mining: Introduction Log in to Mediaspace to watch this video

Covers the challenges and opportunities of data mining, practical questions, algorithm components, and applications like shopping basket analysis.

Digital Humanities and Digitized Press Log in to Mediaspace to watch this video

Explores digitized press archives, text data processing challenges, methodologies for group work, and the societal impact of digital humanities.