Lesson 5: Practical Deep Learning for Coders 2022

00:00:00 - Introduction 00:01:59 - Linear model and neural net from scratch 00:07:30 - Cleaning the data 00:26:46 - Setting up a linear model 00:38:48 - Creating functions 00:39:39 - Doing a gradient descent step 00:42:15 - Training the linear model 00:46:05 - Measuring accuracy 00:48:10 - Using sigmoid 00:56:09 - Submitting to Kaggle 00:58:25 - Using matrix product 01:03:31 - A neural network 01:09:20 - Deep learning 01:12:10 - Linear model final thoughts 01:15:30 - Why you should use a framework 01:16:33 - Prep the data 01:19:38 - Train the model 01:21:34 - Submit to Kaggle 01:23:22 - Ensembling 01:25:08 - Framework final thoughts 01:26:44 - How random forests really work 01:28:57 - Data preprocessing 01:30:56 - Binary splits 01:41:34 - Final Roundup Timestamps thanks to RogerS49 on forums.fast.ai. Transcript thanks to azaidi06, fmussari, wyquek, heylara on forums.fast.ai.