Phase 4: Math → Code Bridge · ~90 minutes · Python
Tensor Operations
Tensors are the common language between data and deep learning. Every image, every sentence, every gradient flows through them.
What you will learn
- Implement a tensor class with shape, strides, reshape, transpose, and element-wise operations from scratch
- Apply broadcasting rules to operate on tensors of different shapes without copying data
- Write einsum expressions for dot products, matrix multiplications, outer products, and batched operations
- Trace the exact tensor shapes through every step of multi-head attention
Introduction
- Type: Build
- Language: Python
- Prerequisites: Linear Algebra Intuition
- Time: ~90 minutes
Objective
Learning objectives
- Implement a tensor class with shape, strides, reshape, transpose, and element-wise operations from scratch
- Apply broadcasting rules to operate on tensors of different shapes without copying data
- Write einsum expressions for dot products, matrix multiplications, outer products, and batched operations
- Trace the exact tensor shapes through every step of multi-head attention
Unlock the full lesson
You've read the first 2 sections. The rest of this lesson covers The Problem, The Concept, Build, Check Yourself, Key Terms & Next — plus a hands-on lab, quiz, and project artifact.
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