This is an open, unconventional textbook covering mathematics, computing, and artificial intelligence from foundational principles. It's designed for practitioners seeking a deep understanding, moving beyond exam preparation and focusing on real-world application. The author, drawing from years of experience in AI/ML, has compiled notes that prioritize intuition, context, and clear explanations, avoiding dense notation and outdated material.
The compendium covers a broad range of topics, from vectors and matrices to machine learning, computer vision, and multimodal learning, with future chapters planned for areas like data structures and AI inference.
The compendium covers a broad range of topics, from vectors and matrices to machine learning, computer vision, and multimodal learning, with future chapters planned for areas like data structures and AI inference.
This book covers foundational topics within computer vision, with an image processing and machine learning perspective. It aims to build the reader’s intuition through visualizations and is intended for undergraduate and graduate students, as well as experienced practitioners.
upervisely, a computer vision platform, has released its latest update, allowing users to train and run the latest deep learning models out of the box. With this release, users can now connect their personal computers or cloud servers to Supervisely and use GPUs to train and run models. The platform also offers a range of features such as sharable links, simplified user permissions, and customizable hotkeys, making it a comprehensive solution for AI projects.
