Deep learning is often considered the exclusive domain of PhDs and large tech companies. However, as this how-to guide shows, programmers familiar with Python can achieve impressive results in deep learning with less experience, less data, and minimal code. how? Fastai is the first library to provide a consistent interface to the most commonly used deep learning applications.
Deep Learning for Coders with Fastai and PyTorch
AI Applications Without a PhD
The creators of fastai, Jeremy Howard and Sylvain Gugger, show how to use fastai and PyTorch to train a model for a variety of problems. We will also dig deeper and deeper into deep learning theory to get a complete understanding of the hidden algorithms.
This book covers
- Train models in computer vision, natural language processing, tabular data, and collaborative filtering
- Learn the latest deep learning techniques that matter most in practice
- Improve accuracy, speed, and reliability by understanding how deep learning models work
- Discover how to turn your models into web applications
- Implement deep learning algorithms from scratch
- Consider the ethical implications of your work
- Gain insight from the foreword by PyTorch cofounder, Soumith Chintala.