Practical Deep Learning for Coders
by fast.ai
Train state-of-the-art models in the first lesson, then learn the theory top-down — the anti-textbook.
Overview
Created by Jeremy Howard and Rachel Thomas, Practical Deep Learning for Coders flips the usual order: you build and train working models — image classifiers, NLP models, tabular and collaborative-filtering systems — from lesson one, and pick up the underlying theory as you go. It uses the fastai library on top of PyTorch and is beloved for making deep learning feel achievable for working programmers. Entirely free, with an accompanying book.
At a Glance
- Topic
- ML
- Level
- Intermediate
- Format
- Course
- Cost
- Free
- Duration
- ~7 lessons, self-paced
- Provider
- fast.ai
- Hands-on
- Yes — code/exercises
- Certificate
- None
What You’ll Learn
- ✓Training image, text, and tabular models fast
- ✓Transfer learning and fine-tuning
- ✓The fastai/PyTorch workflow
- ✓Enough theory to debug and improve models
Highlights
- •Working models from lesson one
- •Top-down, code-first teaching
- •Free, with a companion book and forums
Who It’s For
Best For
- ✓Working programmers who learn by building
Prerequisites
- •Comfortable coding in Python
FAQ
What is Practical Deep Learning for Coders?
fast.ai's famous free course that gets coders training real deep-learning models immediately, with a top-down, code-first pedagogy.
Is Practical Deep Learning for Coders free?
Practical Deep Learning for Coders is free to access.
What level is Practical Deep Learning for Coders for?
Practical Deep Learning for Coders is aimed at a intermediate audience. Recommended background: Comfortable coding in Python.
How long does Practical Deep Learning for Coders take?
Expect roughly ~7 lessons, self-paced. Most learners work through it at their own pace.
What will I learn from Practical Deep Learning for Coders?
You'll learn: Training image, text, and tabular models fast; Transfer learning and fine-tuning; The fastai/PyTorch workflow; Enough theory to debug and improve models.