SMOTE or Synthetic Data for Handling Class Imbalance? I Wrote About It on ThinkML

What's This Post About?

I'm thrilled to share that my latest article has been published on ThinkML, a leading platform for practical insights in Artificial Intelligence and Machine Learning.

The article, titled "Balancing the Imbalance: SMOTE and Synthetic Data Face Off", takes a deep dive into strategies for handling skewed class distributions — a frequent challenge in real-world ML workflows.

🔍 Key Highlights:

• SMOTE: A Closer Look
• Synthetic Data Generation: Beyond SMOTE
• When to Use What: A Practical Decision Guide
• Real-world Considerations & Takeaways

If you're navigating class imbalance in your AI projects or exploring synthetic data techniques, I believe you'll find it valuable.

👉 Read the full, free article here: https://thinkml.ai/balancing-the-imbalance-smote-and-synthetic-data-face-off/