calculus 9
- ⚙️ Optimization in Machine Learning: From Gradient Descent to Newton’s Method
- 🔺 What is the Hessian? Understanding Curvature and Optimization in Machine Learning
- Understanding the Jacobian – A Beginner’s Guide with 2D & 3D Examples
- 🔗 Chain Rule, Implicit Differentiation, and Partial Derivatives (Calculus for ML)
- 📐 Understanding Gradients and Partial Derivatives (Multivariable Calculus for Machine Learning)
- 🔍 What is a Derivative? (Beginner’s Guide to Calculus for ML)
- 🔁 From Limits to Smoothness: Transformations, Limits, Continuity & Differentiability
- 🌄 Visualizing Multivariable Functions: Contour Plots, Vector-Valued Functions & Vector Fields (Beginner's Guide)
- 🧮 Understanding Functions: The Foundation of Calculus (and Machine Learning!)