Lesson 2: Practical Deep Learning for Coders 2022

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.