???? Day 177 of 365: Linear SVMs ????
Ajinkya Deokate
Data Scientist | Researcher | Author | Public Speaking Expert @PlanetSpark | Freelancer
Hey, Data Scientists!
Welcome to Day 177 of our #365DaysOfDataScience journey! ??
I'm excited to explore how tuning the C parameter helps balance accuracy and generalization—let's see how much we can improve by experimenting!
???? Today's Goal:
??- Today, we’ll dive into implementing a **linear SVM** for binary classification!
??- We’ll focus on understanding the important **cost parameter C**, which controls the trade-off between maximizing the margin and minimizing classification errors.
?? Learning Resources:
??- I’ll be reading the **Scikit-learn documentation** on SVC (Support Vector Classification) to get familiar with how SVMs work in Python.
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?? Today’s Task:
??- I'll be implementing an **`SVC` with a linear kernel** on a dataset (maybe the famous Iris dataset!). I’ll also experiment with different values of the C parameter to see how it impacts the model’s performance.
Happy Learning & See You Soon!