Lesson 2: Practical Deep Learning for Coders 2022
Channel: Jeremy Howard
Date: 2022-07-21

Q&A and all resources for this lesson available here: https://forums.fast.ai/t/lesson-2-official-topic/96033

00:00 - Introduction
00:55 - Reminder to use the fastai book as a companion to the course
02:06 - aiquizzes.com for quizzes on the book
02:36 - Reminder to use fastai forums for links, notebooks, questions, etc.
03:42 - How to efficiently read the forum with summarizations
04:13 - Showing what students have made since last week
06:45 - Putting models into production
08:10 - Jupyter Notebook extensions
09:49 - Gathering images with the Bing/DuckDuckGo
11:10 - How to find information & source code on Python/fastai functions
12:45 - Cleaning the data that we gathered by training a model
13:37 - Explaining various resizing methods
14:50 - RandomResizedCrop explanation
15:50 - Data augmentation
16:57 - Question: Does fastai's data augmentation copy the image multiple times?
18:30 - Training a model so you can clean your data
19:00 - Confusion matrix explanation
20:33 - plot_top_losses explanation
22:10 - ImageClassifierCleaner demonstration
25:28 - CPU RAM vs GPU RAM (VRAM)
27:18 - Putting your model into production
30:20 - Git & Github desktop
31:30 - For Windows users
37:00 - Deploying your deep learning model
37:38 - Dog/cat classifier on Kaggle
38:55 - Exporting your model with learn.export 
39:40 - Downloading your model on Kaggle
41:30 - How to take a model you trained to make predictions 
43:30 - learn.predict and timing
44:22 - Shaping the data to deploy to Gradio
45:47 - Creating a Gradio interface
48:25 - Creating a Python script from your notebook with #|export
50:47 - Hugging Face deployed model
52:12 - How many epochs do you train for?
53:16 - How to export and download your model in Google Colab
54:25 - Getting Python, Jupyter notebooks, and fastai running on your local machine
1:00:50 - Comparing deployment platforms: Hugging Face, Gradio, Streamlit
1:02:13 - Hugging Face API
1:05:00 - Jeremy's deployed website example - tinypets
1:08:23 - Get to know your pet example by aabdalla
1:09:44 - Source code explanation
1:11:08 - Github Pages

Thanks to bencoman, mike.moloch, amr.malik, gagan, fmussari, kurianbenoy, and heylara on forums.fast.ai for creating the transcript.

Thanks to Raymond-Wu on forums.fast.ai for creating the timestamps.