Data Mining
Comprehensive exploration of data mining techniques, covering preprocessing, association rules, classification methods, and clustering algorithms for extracting valuable insights from datasets.
Algorithms for Big Data
Explore advanced algorithmic techniques for handling massive datasets, enhancing your ability to process and analyze big data efficiently.
Business Analytics for Management Decision
This course will be exclusively quantitative and an application to business/management-related problems. It is connected with problem sets and real life cases to know the relevance of a particular problem and the decision-making thereof.
Introduction to Analytics and Artificial Intelligence - AI Training for Beginners
Explore analytics and AI fundamentals, covering data mining, business intelligence, and various analytics types. Gain practical insights to enhance your skills in today's data-driven landscape.
Data Mining for Beginners - Learn Data Mining
This video teaches Data Mining and its key functions and concepts with a variety of demonstrations & examples to help you get started on the right foot.
AI, Archaeology, and Archives - How Data Science is Helping to Reveal Past Epidemics
Exploring malaria's impact through data science, integrating archaeological, historical, and genetic datasets to reveal socio-political influences on disease spread over the last 300 years.
Data Mining - The Tool of the Information Age
Explore, analyze, and leverage data sets of any scale with guidance from Google's Search Scientist in this informative webinar on data mining techniques and applications.
Advanced Digital Signal Processing - Multirate and Wavelets
Explore advanced digital signal processing concepts, focusing on multirate systems and wavelets. Learn about filter banks, time-frequency analysis, and various wavelet transforms with practical applications.
Data Mining with Weka
Learn data mining techniques using Weka software. Explore datasets, build classifiers, visualize data, and understand key concepts like cross-validation, overfitting, and ensemble learning.
More Data Mining with Weka
Explore advanced data mining techniques using Weka, covering discretization, document classification, decision trees, association rules, clustering, attribute selection, cost-sensitive learning, and neural networks.
Advanced Data Mining with Weka
Explore advanced data mining techniques using Weka, covering time series forecasting, incremental learning, integration with R and Python, and distributed processing for big data analysis.
EditKG: Editing Knowledge Graph for Recommendation - Lecture 1
Explore innovative techniques for editing knowledge graphs to enhance recommendation systems, focusing on improving accuracy and relevance.
MetaHKG: Meta Hyperbolic Learning for Few-shot Temporal Reasoning - M1.2
Explore meta hyperbolic learning for few-shot temporal reasoning in knowledge graphs, enhancing reasoning capabilities with limited data.
Boundless Analytics Powered by DQL and Grail - Live Demo and Production Insights
Explore Grail and DQL's advanced capabilities for data analysis, including schema-on-read, real-time parsing, and joining diverse data types to streamline operations.
GPT4Rec: Graph Prompt Tuning for Streaming Recommendation - Tutorial 2.5
Explore graph prompt tuning for streaming recommendations using GPT4Rec, enhancing real-time personalized content delivery in dynamic environments.
Optimal Transport Enhanced Cross-City Site Recommendation - T2.4
Explore optimal transport techniques for cross-city site recommendations, enhancing POI suggestions through advanced computational methods.
Graph Signal Diffusion Model for Collaborative Filtering - Tutorial 2.2
Explore graph signal diffusion models for collaborative filtering in recommendation systems, enhancing predictive accuracy and user experience.
Denoising Diffusion Recommender Model - Lecture 2.2
Explore cutting-edge denoising diffusion techniques for recommender systems, enhancing prediction accuracy and user experience in personalized recommendations.
Collaborative Filtering Based on Diffusion Models: Unveiling the Potential of High-Order Connectivity
Explore collaborative filtering using diffusion models, unveiling high-order connectivity potential in recommendation systems for enhanced user experiences.
Lightweight Embeddings for Graph Collaborative Filtering - SIGIR 2024
Explore lightweight embeddings for graph collaborative filtering in recommender systems, enhancing efficiency and performance in user-item interactions.
TransGNN: Harnessing the Collaborative Power of Transformers and Graph Neural Networks for Recommender Systems
Explore TransGNN's fusion of Transformers and Graph Neural Networks for enhanced recommender systems, improving collaborative filtering and user-item interactions.