🌟 Vision Transformer (ViT) Tutorial – Part 1: From CNNs to Transformers – The Revolution in Computer Vision
Let's start: https://hackmd.io/@husseinsheikho/vit-1
Let's start: https://hackmd.io/@husseinsheikho/vit-1
#VisionTransformer #ViT #DeepLearning #ComputerVision #Transformers #AI #MachineLearning #NeuralNetworks #ImageClassification #AttentionIsAllYouNeed
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🌟 Vision Transformer (ViT) Tutorial – Part 2: Implementing ViT from Scratch in PyTorch
Let's start: https://hackmd.io/@husseinsheikho/vit-2
Let's start: https://hackmd.io/@husseinsheikho/vit-2
#VisionTransformer #ViTFromScratch #PyTorch #DeepLearning #ComputerVision #Transformers #AI #MachineLearning #CodingTutorial #AttentionIsAllYouNeed
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🌟 Vision Transformer (ViT) Tutorial – Part 3: Pretraining, Transfer Learning & Real-World Applications
Let's start: https://hackmd.io/@husseinsheikho/vit-3
✉️ Our Telegram channels: https://yangx.top/addlist/0f6vfFbEMdAwODBk
Let's start: https://hackmd.io/@husseinsheikho/vit-3
#VisionTransformer #TransferLearning #HuggingFace #ImageNet #FineTuning #AI #DeepLearning #ComputerVision #Transformers #ModelZoo
✉️ Our Telegram channels: https://yangx.top/addlist/0f6vfFbEMdAwODBk
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🌟 Vision Transformer (ViT) Tutorial – Part 4: Beyond Classification – DETR, Segmentation & Video Transformers
Let's start learn: https://hackmd.io/@husseinsheikho/vit-4
#VisionTransformer #DETR #Segmenter #VideoTransformer #MAE #SelfSupervised #Multimodal #AI #DeepLearning #ComputerVision
Let's start learn: https://hackmd.io/@husseinsheikho/vit-4
#VisionTransformer #DETR #Segmenter #VideoTransformer #MAE #SelfSupervised #Multimodal #AI #DeepLearning #ComputerVision
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🔥 Master Vision Transformers with 65+ MCQs! 🔥
Are you preparing for AI interviews or want to test your knowledge in Vision Transformers (ViT)?
🧠 Dive into 65+ curated Multiple Choice Questions covering the fundamentals, architecture, training, and applications of ViT — all with answers!
🌐 Explore Now: https://hackmd.io/@husseinsheikho/vit-mcq
🔹 Table of Contents
Basic Concepts (Q1–Q15)
Architecture & Components (Q16–Q30)
Attention & Transformers (Q31–Q45)
Training & Optimization (Q46–Q55)
Advanced & Real-World Applications (Q56–Q65)
Answer Key & Explanations
Are you preparing for AI interviews or want to test your knowledge in Vision Transformers (ViT)?
🧠 Dive into 65+ curated Multiple Choice Questions covering the fundamentals, architecture, training, and applications of ViT — all with answers!
🌐 Explore Now: https://hackmd.io/@husseinsheikho/vit-mcq
🔹 Table of Contents
Basic Concepts (Q1–Q15)
Architecture & Components (Q16–Q30)
Attention & Transformers (Q31–Q45)
Training & Optimization (Q46–Q55)
Advanced & Real-World Applications (Q56–Q65)
Answer Key & Explanations
#VisionTransformer #ViT #DeepLearning #ComputerVision #Transformers #AI #MachineLearning #MCQ #InterviewPrep
✉️ Our Telegram channels: https://yangx.top/addlist/0f6vfFbEMdAwODBk
📱 Our WhatsApp channel: https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
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