This course provides a comprehensive understanding of the theory behind Support Vector Machines, including the derivation of Linear SVM, the Kernel SVM using Lagrangian Duality, and the application of Quadratic Programming. It covers practical applications like image recognition and spam detection.
Structured path covering Python, ML fundamentals, and deep learning basics for aspiring AI practitioners.
Your first steps into machine learning. Understand supervised and unsupervised learning, train your first models, and build intuition for how algorithms learn from data.
Build on your existing knowledge with intermediate machine learning techniques and real-world applications.
Master advanced machine learning concepts with expert-level content and cutting-edge techniques.
Start your journey into computer vision with foundational concepts and hands-on exercises designed for newcomers.
Build on your existing knowledge with intermediate computer vision techniques and real-world applications.
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