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Learn to build an AI model from scratch using Vision Transformers (ViTs) to detect trading candlesticks in this comprehensive tutorial. Explore the complete development process of implementing a computer vision solution for financial market analysis, covering data preparation, model architecture design, and training procedures. Master the fundamentals of Vision Transformers while working on a practical trading application that identifies different candlestick patterns. Discover advanced techniques including data augmentation with ColorJitter, CutMix, and Mixup transformations to improve model performance. Gain hands-on experience with PyTorch implementation, utilizing libraries like Albumentations for image preprocessing and Lucid Rain's ViT implementation. Follow along with the complete coding workflow, from initial setup through model training and evaluation, while learning to overcome common challenges in computer vision projects. Access the accompanying GitHub repository for full source code and continue development as part of an ongoing live project with community support and updates.
