Lectures related to Association Rule Mining

Association Rules: Frequent Itemsets

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

FP-Growth: Itemset Mining

Introduces the FP-Growth algorithm for mining frequent itemsets in transaction datasets.

Association Rules: Mining and Algorithms

Explores Association Rule Mining, Apriori algorithm, and rule generation using support and confidence.

Data Mining: Introduction

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

Algorithms in Computer Science: Search and Sort Techniques

Provides an overview of essential search and sort algorithms in computer science.

Association Rules Mining

Covers association rules mining, focusing on Apriori and FP-growth algorithms to find frequent itemsets and extract rules efficiently.

Association Rules

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

Programming Concepts: Variables and Expressions

Covers fundamental programming concepts such as algorithms, variables, and expressions in C++.

Graph Mining: Social Networks and Data Analysis

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

Standard Library: Containers and Algorithms

Explores C++ standard library containers and algorithms, including associative tables, stacks, queues, and random number generation.

Information Retrieval: Indexing and Retrieval

Covers indexing techniques, distributed retrieval algorithms, and challenges in large-scale web indexing.

Matrix Multiplication and Divide-and-Conquer Techniques

Discusses matrix multiplication using divide-and-conquer techniques and introduces Strassen's algorithm for improved efficiency.

Designing Algorithms: Recursion and Dynamic Programming

Explores designing algorithms with recursion and dynamic programming, covering concepts like the Towers of Hanoi and efficient solutions.

Introduction to Algorithms: Course Overview and Basics

Introduces the CS-250 Algorithms course, covering its structure, objectives, and key topics in algorithmic problem-solving.

Python Programming: Lists and Functions Overview

Introduces Python programming concepts, focusing on lists, functions, and their applications in problem-solving.

Distributed Information Systems: Course Overview

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

Overview: Information Management

Explores levels of data abstraction, model building, usage, and representation, and the utility of information systems for decision-making.

Introduction to Algorithms: Basics and Importance

Covers the basics of algorithms, the importance of studying them, data structures, and the impact of algorithms on various fields.

Introduction to Algorithms

Introduces the importance of studying algorithms, presents a clever algorithm for calculating an arithmetic series, and discusses efficiency and correctness in algorithms.

C++ Standard Library: Containers and Algorithms

Covers the basics of C++ standard library containers, algorithms, and iterators.