Linear Algebra for AI/ML (Part 1) — Vectors, Matrices & Dot Product with NumPy Programming скачать в хорошем качестве

Linear Algebra for AI/ML (Part 1) — Vectors, Matrices & Dot Product with NumPy Programming

🚀 Linear Algebra is the backbone of Artificial Intelligence and Machine Learning — and this video is your complete beginner-friendly starting point. In this video, we learn the most important Linear Algebra concepts used in AI/ML with clear intuition and practical NumPy implementation. This is Part 1 of the “Linear Algebra for AI/ML” series where we build the mathematical foundation required to truly understand how AI models work. 📚 Topics Covered: ✅ What is a Vector in Machine Learning ✅ Matrix Representation of Dataset ✅ Dot Product (Real Math Behind AI Prediction) ✅ Matrix Multiplication Explained ✅ Transpose in Linear Algebra ✅ Vector Norms & Distance Measurement ✅ NumPy Programming Step-by-Step 💻 All concepts are explained with practical Python & NumPy examples so beginners can connect math with real AI applications. 🎯 After this video, you will understand: • How data is represented inside AI models • Why matrices are used in Machine Learning • How prediction math actually works • The foundation of neural networks -------------------------------------------------- 🧠 Who is this for? • AI & Machine Learning beginners • Python & NumPy learners • Data Science students • Anyone starting Deep Learning journey -------------------------------------------------- 📌 Tech Stack: Python | NumPy | Linear Algebra | Machine Learning Basics #LinearAlgebra #MachineLearning #ArtificialIntelligence #NumPy #PythonForAI #AIMath #DataScience #DeepLearning #aiforbeginners #reels #education #python