Foundations of Vector Retrieval by Sebastian Bruch (.PDF)

File Size: 10 MB

Foundations of Vector Retrieval by Sebastian Bruch
Requirements: .PDF reader, 10 MB
Overview: This book presents the fundamentals of vector retrieval. To this end, it delves into important data structures and algorithms that have been successfully used to solve the vector retrieval problem efficiently and effectively. We are witness to a few years of remarkable developments in Artificial Intelligence (AI) with the use of advanced machine learning algorithms, and in particular, Deep Learning. Gargantuan, complex neural networks that can learn through self-supervision—and quickly so with the aid of specialized hardware—transformed the research landscape so dramatically that, overnight it seems, many fields experienced not the usual, incremental progress, but rather a leap forward. Machine translation, natural language understanding, information retrieval, recommender systems, and Computer Vision are but a few examples of research areas that have had to grapple with the shock. Countless other disciplines beyond Computer Science such as robotics, biology, and chemistry too have benefited from Deep Learning. These neural networks and their training algorithms may be complex, and the scope of their impact broad and wide, but nonetheless they are simply functions in a high-dimensional space. A trained neural network takes a vector as input, crunches and transforms it in various ways, and produces another vector, often in some other space.
Genre: Non-Fiction > Tech & Devices

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