???? Day 176 of 365: Introduction to SVMs (Support Vector Machines) ????
Ajinkya Deokate
Data Scientist | Researcher | Author | Public Speaking Expert @PlanetSpark | Freelancer
Hey, Learners!
Welcome to Day 176 of our #365DaysOfDataScience journey! ??
Feel free to jump in and ask questions as we go along! Let's get ready to explore the power of SVMs together! ??
?? Today's Plan:
- What are SVMs? We’ll dive into the concept of SVMs and how they work by finding the "best" boundary (or hyperplane) to classify data points.
- Support Vectors are those important data points that help define this hyperplane.
- Linear vs. Non-linear SVMs: We’ll also explore the difference between simple linear models and more complex non-linear ones.
?? Learning Resources:
- ?? Pattern Recognition and Machine Learning by Christopher Bishop (Chapter on SVMs).
- ?? Watch: "Support Vector Machines Explained" on YouTube for a clear, visual breakdown.
?? Today’s Task:
- Today’s focus is on grasping the theory. Take time to absorb the ideas behind SVMs, and jot down your key takeaways as we explore these fascinating models!
Happy Learning & See You Soon!