Post by Shivani khanna

Over the past few weeks, I’ve been learning the AI Product Management and sharing my learnings through LinkedIn posts. One challenge I noticed was that the concepts were spread across multiple posts, which made it difficult to revisit them in one place. Many of you also suggested compiling everything together for easier reference. Taking that feedback into account, I’ve created a simple AIPM handbook with clear explanations, key formulas, and practical examples. I’ve organized the material into parts so it’s easier to consume. Sharing Part 1 today. Part 1 covers: • ML fundamentals (AI → Machine Learning → Deep Learning) • The ML workflow using the CRISP-DM framework • Bias vs Variance and model complexity • Regression metrics (MAE, MSE, MAPE, R²) • Classification metrics (Precision, Recall, ROC Curve, Confusion Matrix) The goal was to keep the language simple and beginner-friendly, so it can serve as a quick reference for anyone starting their AI journey. Would love your feedback and suggestions as I continue building the next parts. #MachineLearning #AI #LearningInPublic #AIPM #PM #APM #LLMs #ProductManager #AIProductManager #ProductOwner