It stands as an indispensable resource for any scientist keen on integrating machine learning effectively into their research.Numerous... Læs mere
The book focuses on model-based empirical methods where data annotations and model predictions are treated as training data for interpretable probabilistic models from the well-understood families of generalized additive models (GAMs) and linear mixed effects models (LMEMs).
This book introduces a new type of data poisoning attack, dubbed, backdoor attack.
This book focuses on a wide range of distributed machine learning and computing algorithms and their applications in healthcare and... Læs mere
Second, it describes several novel deep learning algorithms for solving challenging problems in computational physics, thereby offering someone who is interested in modeling physical phenomena with a complementary set of tools.
It covers a range of topics including the basics of AI, ML, and blockchain, the application of AI and ML in cybersecurity, the use of blockchain in cybersecurity, and the integrationof AI, ML, and blockchain in cybersecurity systems.
It typically includes model selection, parameter tuning and optimization, use of pre-trained models and transfer learning, right use of... Læs mere
This book delves into practical implementation of evolutionary and metaheuristic algorithms to advance the capacity of machine... Læs mere
Over the past decade, Artificial Intelligence has proved invaluable in a range of industry verticals such as automotive and assembly, life sciences, retail, oil and gas, and travel.