Learning PyTorch 2.0: Experiment deep learning from basics to complex models using every potential c

Dreyfus, Hubert

Brockman, John

Bender, Emily M

Edelkamp, Stefan

Chen, Yaobin

<p>Plan recognition, activity recognition, and intent recognition together combine and unify techniques from user modeling, machine vision, intelligent user interfaces, human/computer interaction, autonomous and multi-agent systems, natural language understanding, and machine learning. </p> <i> <p>Plan, Activity, and Intent Recognition</i> explains the crucial role of these techniques in a wide variety of applications including: </p> <ul> <li>personal agent assistants </li> <li>computer and network security </li> <li>opponent modeling in games and simulation systems </li> <li>coordination in robots and software agents </li> <li>web e-commerce and collaborative filtering </li> <li>dialog modeling </li> <li>video surveillance </li> <li>smart homes </li></ul> <p>In this book, follow the history of this research area and witness exciting new developments in the field made possible by improved sensors, increased computational power, and new application areas.</p>