Deep Learning for Coders with fastai & PyTorch

My notes from the book Deep Learning for Coders with fastai & PyTorch: AI Applications without a PhD by Jeremy Howard and Sylvain Gugger.
Published

March 14, 2022

Notes on fastai Book Ch. 1

ai
fastai
notes
pytorch

Chapter 1 covers the history of artificial neural networks, approaches for learning ML/DL, and using the fast.ai library for multiple deep learning tasks.
Mar 14, 2022
35 min

Notes on fastai Book Ch. 2

ai
fastai
notes
pytorch

Chapter 2 covers how to train an image classification model using a custom dataset and turn it into an online application.
Mar 14, 2022
23 min

Notes on fastai Book Ch. 3

ai
ethics
fastai
notes

Chapter 3 defines data ethics, introduces essential topics in data ethics, and explains how to identify and address ethical issues.
Mar 14, 2022
16 min

Notes on fastai Book Ch. 4

ai
fastai
notes
pytorch

Chapter 4 covers broadcasting, stochastic gradient descent, the MNIST loss function, and the sigmoid activation functions.
Mar 14, 2022
84 min

Notes on fastai Book Ch. 5

ai
fastai
notes
pytorch

Chapter 5 covers creating a custom DataBlock for an image classifier, pre-sizing, cross-entropy loss, model interpretation, picking learning rates, transfer learning, and discriminative learning rates.
Mar 14, 2022
33 min

Notes on fastai Book Ch. 6

ai
fastai
notes
pytorch

Chapter 6 covers multi-label classification and image regression.
Mar 14, 2022
20 min

Notes on fastai Book Ch. 7

ai
fastai
notes
pytorch

Chapter 7 covers data normalization, progressive resizing, test-time augmentation, mixup, and label smoothing.
Mar 14, 2022
26 min

Notes on fastai Book Ch. 8

ai
fastai
notes
pytorch

Chapter 8 provides a deep dive into collaborative filtering.
Mar 28, 2022
43 min

Notes on fastai Book Ch. 09

ai
fastai
notes
pytorch

Chapter 9 provides a deep dive into tabular modeling.
Mar 29, 2022
58 min

Notes on fastai Book Ch. 10

ai
fastai
notes
pytorch

Chapter 10 covers text preprocessing and training an RNN for text classification.
Mar 29, 2022
49 min

Notes on fastai Book Ch. 11

ai
fastai
notes
pytorch

Chapter 11 covers data munging with fast.ai’s mid-level data API.
Mar 29, 2022
49 min

Notes on fastai Book Ch. 12

ai
fastai
notes
pytorch

Chapter 12 covers building and training an LSTM from scratch.
Mar 29, 2022
49 min

Notes on fastai Book Ch. 13

ai
fastai
notes
pytorch

Chapter 13 provides a deep dive into convolutional neural networks.
Mar 29, 2022
59 min

Notes on fastai Book Ch. 14

ai
fastai
notes
pytorch

Chapter 14 covers building a ResNet from scratch.
Mar 29, 2022
43 min

Notes on fastai Book Ch. 15

ai
fastai
notes
pytorch

Chapter 15 provides a deep dive into different application architectures in the fast.ai library.
Mar 29, 2022
19 min

Notes on fastai Book Ch. 16

ai
fastai
notes
pytorch

Chapter 16 covers momentum, RMSProp, Adam, decoupled weight decay, and fast.ai callbacks.
Mar 29, 2022
36 min

Notes on fastai Book Ch. 17

ai
fastai
notes
pytorch

Chapter 17 covers building a neural network from the foundations.
Mar 29, 2022
33 min

Notes on fastai Book Ch. 18

ai
fastai
notes
pytorch

Chapter 18 covers interpreting convolutional neural networks using class-activation maps.
Mar 29, 2022
13 min

Notes on fastai Book Ch. 19

ai
fastai
notes
pytorch

Chapter 19 covers creating a fast.ai Learner from scratch.
Mar 29, 2022
46 min
No matching items