---
layout: farshid_default
title: "Full Stack Deep Learning"
permalink: /notes/courses/full-stack-dl/
description: "Full Stack Deep Learning course notes covering ML production from data to deployment."
---

Full Stack Deep Learning course notes covering ML production from data to deployment.

# Full Stack Deep Learning

Full Stack Deep Learning (fullstackdeeplearning.com) — Notes for week 1 to week 12 (2021)

Reference: [https://fullstackdeeplearning.com/spring2021](https://fullstackdeeplearning.com/spring2021)

## Underfitting vs Overfitting

**Underfitting (reducing bias):**
- Bigger model
- Reduce regularization
- Error analysis
- Different model architecture
- Tune hyper-parameters
- Add features

**Overfitting (reducing variance):**
- Add more training data
- Add normalization (batch norm, layer norm)
- Add data augmentation
- Increase regularization (dropout, L2, weight decay)
- Error analysis
- Choose different model architecture
- Tune hyper-parameters
- Early stopping
- Remove features
- Reduce model size

#StackDeepLearning #computervision #AI #deeplearning