Swin transformer - Explained!
Summary
This video explains Swin Transformers, a significant and advanced neural network architecture used in deep learning for computer vision. It breaks down what Swin Transformers are, their purpose, and their structure. This content is highly valuable for students and educators who are learning about cutting-edge AI/ML concepts and models.
Description
In this video, we take a look at Swin Transformers. What is it? Why do we have it? How does it look? ABOUT ME ⭕ Subscribe: https://www.youtube.com/c/CodeEmporium?sub_confirmation=1 📚 Medium Blog: https://medium.com/@dataemporium 💻 Github: https://github.com/ajhalthor 👔 LinkedIn: https://www.linkedin.com/in/ajay-halthor-477974bb/ RESOURCES [1 📚] Main Paper: https://arxiv.org/pdf/2103.14030 [2 📚] Slides: https://link.excalidraw.com/p/readonly/GDnU1EEBGfAyUoEtVyj8 [3 📚] Feature Pyramid Networks: https://youtu.be/i4GKvPGoGxY?si=fgWUV1DYQH3YeU-6 [4 📚] Playlist of Transformers from scratch: https://youtu.be/QCJQG4DuHT0?si=UllVN6odQKC-nsvb [5 📚] Faster R-CNN: https://youtu.be/ws0nlxCWWI8?si=om9yCa-mKWxTtFmQ [6 📚] DETR: https://youtu.be/r3lDNWYDGF4?si=N4XehrgljW0A7XPQ PLAYLISTS FROM MY CHANNEL ⭕ Reinforcement Learning: https://youtube.com/playlist?list=PLTl9hO2Oobd9kS--NgVz0EPNyEmygV1Ha&si=AuThDZJwG19cgTA8 Natural Language Processing: https://youtube.com/playlist?list=PLTl9hO2Oobd_bzXUpzKMKA3liq2kj6LfE&si=LsVy8RDPu8jeO-cc ⭕ Transformers from Scratch: https://youtube.com/playlist?list=PLTl9hO2Oobd_bzXUpzKMKA3liq2kj6LfE ⭕ ChatGPT Playlist: https://youtube.com/playlist?list=PLTl9hO2Oobd9coYT6XsTraTBo4pL1j4HJ ⭕ Convolutional Neural Networks: https://youtube.com/playlist?list=PLTl9hO2Oobd9U0XHz62Lw6EgIMkQpfz74 ⭕ The Math You Should Know : https://youtube.com/playlist?list=PLTl9hO2Oobd-_5sGLnbgE8Poer1Xjzz4h ⭕ Probability Theory for Machine Learning: https://youtube.com/playlist?list=PLTl9hO2Oobd9bPcq0fj91Jgk_-h1H_W3V ⭕ Coding Machine Learning: https://youtube.com/playlist?list=PLTl9hO2Oobd82vcsOnvCNzxrZOlrz3RiD MATH COURSES (7 day free trial) 📕 Mathematics for Machine Learning: https://imp.i384100.net/MathML 📕 Calculus: https://imp.i384100.net/Calculus 📕 Statistics for Data Science: https://imp.i384100.net/AdvancedStatistics 📕 Bayesian Statistics: https://imp.i384100.net/BayesianStatistics 📕 Linear Algebra: https://imp.i384100.net/LinearAlgebra 📕 Probability
