Artificial Intelligence and Data Science Algorithms in Python for Classification and Regression
Master key concepts and practical skills through structured learning modules. By completing this curriculum, you'll gain valuable expertise applicable to real-world scenarios.
Apply SVMs to practical applications: image recognition, spam detection, medical diagnosis, and regression analysis
Understand the theory behind SVMs from scratch (basic geometry)
Use Lagrangian Duality to derive the Kernel SVM
Understand how Quadratic Programming is applied to SVM
Support Vector Regression
This comprehensive Machine Learning and AI: Support Vector Machines in Python curriculum is designed to take you from foundational concepts to advanced implementation. Each module builds upon the previous, ensuring a structured learning path that maximizes knowledge retention and practical application.
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What you need before starting this Machine Learning and AI: Support Vector Machines in Python course:
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Everything you need to know about this online course, from duration to certification
Course Instructor
Lazy Programmer Inc.
Expert instructor with industry experience
Course Language
English
All materials in English
This online course offers comprehensive training with expert instruction, practical exercises, and a certificate of completion. Join thousands of students advancing their careers through quality online education.
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