Understanding Deep Learning Research Tutorial - Theory, Code and Math

Curriculum for the course Understanding Deep Learning Research Tutorial - Theory, Code and Math

If 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 🎉 Thanks to our Champion and Sponsor supporters: 👾 Drake Milly 👾 Ulises Moralez 👾 Goddard Tan 👾 David MG 👾 Matthew Springman 👾 Claudio 👾 Oscar R. 👾 jedi-or-sith 👾 Nattira Maneerat 👾 Justin Hual -- Learn to code for free and get a developer job: https://www.freecodecamp.org Read hundreds of articles on programming: https://freecodecamp.org/news

Watch Online Full Course: Understanding Deep Learning Research Tutorial - Theory, Code and Math

Click Here to watch on Youtube: Understanding Deep Learning Research Tutorial - Theory, Code and Math

This video is first published on youtube via freecodecamp. If Video does not appear here, you can watch this on Youtube always.

Udemy Understanding Deep Learning Research Tutorial - Theory, Code and Math courses free download, Plurasight Understanding Deep Learning Research Tutorial - Theory, Code and Math courses free download, Linda Understanding Deep Learning Research Tutorial - Theory, Code and Math courses free download, Coursera Understanding Deep Learning Research Tutorial - Theory, Code and Math course download free, Brad Hussey udemy course free, free programming full course download, full course with project files, Download full project free, College major project download, CS major project idea, EC major project idea, clone projects download free