name: "Loss Functions"
number: 5
description: "Essential loss functions for neural network training objectives"
learning_objectives:
  - "Implement MSE, CrossEntropy, and BinaryCrossEntropy loss functions"
  - "Understand numerical stability in loss computation"
  - "Match loss functions to problem types (regression vs classification)"
  - "Build production-ready loss functions with batch processing"
prerequisites:
  - "02_tensor"
difficulty: "⭐⭐⭐"
time_estimate: "2-3 hours"
exports:
  - "MeanSquaredError"
  - "CrossEntropyLoss" 
  - "BinaryCrossEntropyLoss"
key_concepts:
  - "Training objectives and optimization"
  - "Numerical stability in loss computation"
  - "Regression vs classification loss functions"
  - "Batch processing for scalable training"