Overview

Are you tired of using computationally expensive and unstable machine learning models? Do you struggle to detect and prevent cyber-attacks, spam, and malware? If you need powerful, safe and efficient solutions that can accurately classify and predict in real-time, Support Vector Machines (SVMs) are here to help!

This course is your key to mastering advanced SVM techniques in the shortest time frame possible. The course covers everything you need to know from data manipulation and analysis with popular Python libraries to the foundations of Support Vector Machines and their kernel extensions. With a focus on practicality, you'll be well-prepared to leverage these models for classification and regression problems with applications to security and more.

During this course, you get introduced to the exciting world of Support Vector Machines (SVM). You will also understand Support Vector Machines and explain their importance in the domain of machine learning. You will also be introduced to hyperplanes, margins and loss functions. Understanding these concepts will be crucial to building a strong foundation in SVMs to apply them to a wide range of problems. You will also be focusing on use-cases like malware detection and spam filtering, process of model training, evaluation, and fine-tuning SVM hyperparameters for optimal performance.

By the end of the course, you would have developed hands-on skills to secure what matters most to you, in the ever-evolving landscape of threats.