As Machine Learning and AI technologies continue to advance, the need for efficient and secure methods to store, share, and deploy trained models becomes increasingly critical. Model weights file ...
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Unsloth: A Guide from Basics to Fine-Tuning Vision Models
Unsloth has emerged as a game-changer in the world of large language model (LLM) fine-tuning, addressing what has long been a resource-intensive and technically complex challenge. Adapting models like ...
Understanding Iterative Closest Point (ICP) Algorithm with Code
Iterative Closest Point (ICP) is a widely used classical computer vision algorithm for 2D or 3D point cloud registration. As the name suggests it iteratively improves and minimizes the spatial ...
MedSAM2 Explained: One Prompt to Segment Anything in Medical Imaging
Evening rush hour, a small country hospital, the scan room hums like an old fridge while a tired doctor checks the last patient of the day - a farmer who fell off his tractor and now finds it hard to ...
Batch Normalization and Dropout: A Combined Regularization Approach
In Deep Learning, Batch Normalization (BatchNorm) and Dropout, as Regularizers, are two powerful techniques used to optimize model performance, prevent overfitting, and speed up convergence. While ...
DINOv2 by Meta: A Self-Supervised foundational vision model
The field of computer vision is fueled by the remarkable progress in self-supervised learning. At the forefront of this revolution is DINOv2, a cutting-edge self-supervised vision transformer ...
