Understanding Deep Learning Research Tutorial - Theory, Code and Math
1,797If you've ever felt intimidated by deep learning research papers with their dense mathematical notation and complex code bases, this comprehensive tutorial from @deeplearningexplained will show you how to effectively understand and implement cutting-edge AI research. Through practical examples using recent papers, you'll learn the three essential skills needed to master deep learning research: reading technical papers, understanding mathematical notation, and navigating research code bases.
⭐ ️ Contents ⭐ ️
⌨ ️ (0:00:00) Introduction
⌨ ️ (0:01:57) Section 1 - How to read research paper?
⌨ ️ (0:03:49) Section 1 - Step 1 Get External Context
⌨ ️ (0:04:51) Section 1 - Step 2 First Casual Read
⌨ ️ (0:06:01) Section 1 - Step 3 Fill External Gap
⌨ ️ (0:06:28) Section 1 - Step 4 Conceptual Understanding
⌨ ️ (0:07:41) Section 1 - Step 5 Code Deep Dive
⌨ ️ (0:08:29) Section 1 - Step 6 Method and Result Slow Walk
⌨ ️ (0:09:56) Section 1 - Step 7 Weird Gap Identification
⌨ ️ (0:10:28) Section 2 - How to read Deep Learning Math?
⌨ ️ (0:11:22) Section 2 - Step 0 : relax
⌨ ️ (0:12:02) Section 2 - Step 1 : identify all formula shown or referred
⌨ ️ (0:12:38) Section 2 - Step 2 : take the formulas out of the digital world
⌨ ️ (0:13:07) Section 2 - Step 3 : work on them to translate symbols into meaning (QHAdam)
⌨ ️ (0:36:57) Section 2 - Step 4 : summarize the meanings into an intuition
⌨ ️ (0:37:25) Section 3 - How to learn math efficiently
⌨ ️ (0:44:31) Section 3 - Step 1 - Select the right math sub field
⌨ ️ (0:45:03) Section 3 - Step 2 - Find exercise-rich resource
⌨ ️ (0:45:23) Section 3 - Step 3 - green, yellow and red method
⌨ ️ (0:48:09) Section 3 - Step 4 - study the theory to fix yellow and red
⌨ ️ (0:49:49) Section 4 - How to read deep learning codebase?
⌨ ️ (0:50:25) Section 4 - Step 0 Read the paper
⌨ ️ (0:50:47) Section 4 - Step 1 Run the code
⌨ ️ (0:53:16) Section 4 - Step 2 Map the codebase structure
⌨ ️ (0:56:47) Section 4 - Step 3 Elucidate all the components
⌨ ️ (1:03:13) Section 4 - Step 4 Take notes of unclear elements
⌨ ️ (1:03:41) Section 5 - Segment Anything Model Deep Dive
⌨ ️ (1:04:27) Section 5 - Task
⌨ ️ (1:08:50) Section 5 - SAM Testing
⌨ ️ (1:13:32) Section 5 - Model Theory
⌨ ️ (1:17:14) Section 5 - Model Code Overview
⌨ ️ (1:23:46) Section 5 - Image Encoder Code
⌨ ️ (1:25:25) Section 5 - Prompt Encoder Code
⌨ ️ (1:28:33) Section 5 - Mask Decoder Code
⌨ ️ (1:40:21) Section 5 - Data & Engine
⌨ ️ (1:42:47) Section 5 - Zero-Shot Results
⌨ ️ (1:45:21) Section 5 - Limitation
⌨ ️ (1:45:53) Conclusion
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