WEEK 10: DEEP LEARNING PRIMER

Introduction to deep learning, neural networks, and TensorFlow

November 17, 2025

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Weekly Materials

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Lecture Slides

Professor's main lecture presentation

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TA Practice Slides

Hands-on tutorials and practice exercises

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Lesson Guide

Comprehensive explanations and theory

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Code Examples

Multi-layer Perceptron Gradient Descent & SGD MLP Notebook Gentle Introduction to DNNs Function Approximation

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References & Resources

Deep Learning Book Goodfellow, Bengio, and Courville

TensorFlow Documentation Official TensorFlow guides and tutorials

Additional Notes

Week 10: Deep Learning Primer

Topics Covered

• Deep learning basics
• Multi-layer perceptron
• Feed-forward networks
• Network training - SGD
• Error back-propagation
• Some notes on overfitting
• Introduction to TensorFlow, applied to supervised machine learning problems

Code Examples

This week includes implementations of neural networks from scratch and using TensorFlow, demonstrating fundamental deep learning concepts.

Practical Applications

Learn to build, train, and evaluate neural networks for various supervised learning tasks.