CS5720 - Week 1 Summary & Week 2 Preview

Week 1: What We've Learned

🧠

Neural Networks Fundamentals

From biological inspiration to artificial neurons

⚡

The Perceptron

Simplest neural network and its limitations

🔗

Multi-Layer Perceptrons

Building deeper networks for complex problems

📈

Activation Functions

Non-linearity for powerful representations

➡️

Forward Propagation

How data flows through the network

🎯

The Learning Problem

How neural networks learn from data

📉

Loss Functions

Measuring and minimizing errors

⛰️

Gradient Descent

The optimization algorithm that powers learning

🔄

Backpropagation

The magic behind neural network training

💻

Hands-On Training

Build and train your first neural network!