Dimensionality Reduction Lecture
Nowadays, Artificial Intelligence drives scientific and economic growth worldwide. This is largely due to advances in Machine Learning (ML). Its applications span and revolutionize almost every human activity:
-Autonomous Systems (cars, drones, vessels),
-Media Content and Art Creation (including fake data creation/detection), Social Media Analytics,
-Medical Imaging and Diagnosis,
-Financial Engineering (forecasting and analytics), Big Data Analytics,
-Broadcasting, Internet and Communications,
-Robotics/Control
-Intelligent Human-Machine Interaction, Anthropocentric (human-centered) Computing,
-Smart Cities/Buildings and Assisted living.
-Scientific Modeling and Analytics.
This lecture overviews Dimensionality Reduction that has many applications in object clustering and object recognition. It covers the following topics in detail: Feature selection. Principal Component Analysis. Linear Discriminant Analysis. SVD Data Compression. Multidimensional Scaling. Non-negative matrix factorization, Learning Vector Quantization.