From Vectors to Vision - Master Linear Algebra for Smarter ML Models

10 Jul 2025 05:30 AM CST

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Webinar Overview

This webinar explores the foundational role of linear algebra in machine learning. Attendees will learn how concepts like vectors, matrices, and eigenvalues power core algorithms such as linear regression, PCA, and neural networks. Designed for ML beginners and aspiring data scientists, the session connects the math to real-world machine learning workflows with clear, intuitive examples.

Key Points

What is Linear Algebra and Why It Matters in ML
Vectors, Matrices, and Dot Products Explained
Matrix Operations in ML Models
Eigenvalues and PCA for Dimensionality Reduction

Meet The Trainer

Aman Kumar

Multidisciplinary AI and Software Developer, adept in LLM training and optimizing SFT and RLHF workflows for companies like Google and Amazon. Specializes in simplifying AI processes, leading teams, and creating scalable, cloud-integrated products. Committed to inclusive AI and next-gen education.

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