Mathematical Foundation Behind AI/ML
We know that Machine learning is all about math. To truly understand ML we need to understand several key mathematical concepts: Linear Algebra, Calculus, Probability & Statistics, Optimization, Discrete Mathematics & Logic, Information theory But why are these concepts important? Before diving into the mathematical depth of AI/ML let's first understand the basics of Machine learning. The most important ingredient of machine learning is data . “No data, no ML.” To build a Machine Learning model, the first step is to define a goal —like predicting house prices, recognizing faces in photos, or classifying emails. Then we need some data, an algorithm to learn from the data, and an optimization technique to fine-tune the model parameters. All of this leads us to a well-performing model ready for deployment and capable of making predictions on new data. Let's visualize the AI/ML pipeline: Data → Algorithm → Optimization → M...