2025

• 23 Jun ⚙️ Optimization in Machine Learning: From Gradient Descent to Newton’s Method
• 22 Jun 🔺 What is the Hessian? Understanding Curvature and Optimization in Machine Learning
• 21 Jun Understanding the Jacobian – A Beginner’s Guide with 2D & 3D Examples
• 20 Jun 🔗 Chain Rule, Implicit Differentiation, and Partial Derivatives (Calculus for ML)
• 19 Jun 📐 Understanding Gradients and Partial Derivatives (Multivariable Calculus for Machine Learning)
• 18 Jun 🔍 What is a Derivative? (Beginner’s Guide to Calculus for ML)
• 17 Jun 🔁 From Limits to Smoothness: Transformations, Limits, Continuity & Differentiability
• 16 Jun 🌄 Visualizing Multivariable Functions: Contour Plots, Vector-Valued Functions & Vector Fields (Beginner's Guide)
• 15 Jun 🧮 Understanding Functions: The Foundation of Calculus (and Machine Learning!)
• 24 May Sampling Distribution of the Sample Proportion
• 24 May Population, Sample, and Sampling Distributions Explained
• 23 May Understanding the Sampling Distribution of the Sample Mean and the Central Limit Theorem
• 22 May From Sample to Population: Basics of Sampling in Statistics
• 21 May Understanding Binomial Distribution
• 20 May Understanding Z-Distribution and Using the Z-Table
• 19 May Understanding Normal Distribution
• 18 May Mean, Variance, and Standard Deviation of Random Variables
• 17 May What Are Random Variables and How Do We Visualize Their Distributions?
• 16 May Understanding Independence and Bayes’ Rule
• 15 May Making Sense of Probabilities: Union, Tables, and Conditional Thinking
• 14 May How Random Is Random? Understanding Probability and Events
• 13 May Regression: Predicting Relationships Between Variables with the Best Fit Line
• 12 May Pearson’s r: Measuring the Strength and Direction of Linear Relationships
• 11 May Conditional vs. Marginal Proportions: What’s the Difference?
• 10 May Correlation Between Variables: Contingency Tables and Scatter Plots
• 09 May Bringing It All Together: A Real-World Stats Example
• 08 May Z-Score: Comparing Values Using Standardization
• 07 May Measuring Variability: Variance and Standard Deviation
• 06 May Understanding Dispersion: Range, IQR, and the Box Plot
• 05 May Measuring the Center: Mean, Median, and Mode Explained
• 04 May How to Build Frequency Tables in Python (With Charts)
• 03 May Choosing the Right Graph: How to Visualize Your Data in Statistics
• 02 May From Raw Data to Insight: Cases, Variables, and Frequency Tables
• 01 May Descriptive vs Inferential Statistics – A Simple Start