As the increased demand for high-speed communication creates an interest in the development of optical networks, intelligent all optical networks have emerged as the next generation for reliable and fast connections.
Every AI system needs to interact with humans and AI is affecting nearly every human engagement with digital technology from simple word processors to autonomous vehicles.
Every AI system needs to interact with humans and AI is affecting nearly every human engagement with digital technology from simple word processors to autonomous vehicles.
In today's AI landscape, success depends not just on prompting large language models but on orchestrating them into intelligent systems that are scalable, compliant, and cost-effective.
Build and deploy AI-driven trading systems using the 7-Stage workflow with pandas, Polars, LightGBM, PyTorch, Optuna, zipline-reloaded, MLflow, Feast, and SHAPKey FeaturesBuild point-in-time pipelines, integrate alternative data, and ensure data integrityBuild and validate predictive models using GBMs, Transformers, and causal inference frameworks to create robust, interpretable alpha signalsDeploy RAG systems, autonomous financial agents, and diffusion-based synthetic data generatorsBook DescriptionThe rapid rise of AI and the growing complexity of financial markets have transformed quantitative trading into a data-driven, process-oriented discipline.
Build and deploy AI-driven trading systems using the 7-Stage workflow with pandas, Polars, LightGBM, PyTorch, Optuna, zipline-reloaded, MLflow, Feast, and SHAPKey FeaturesBuild point-in-time pipelines, integrate alternative data, and ensure data integrityBuild and validate predictive models using GBMs, Transformers, and causal inference frameworks to create robust, interpretable alpha signalsDeploy RAG systems, autonomous financial agents, and diffusion-based synthetic data generatorsBook DescriptionThe rapid rise of AI and the growing complexity of financial markets have transformed quantitative trading into a data-driven, process-oriented discipline.
In today's AI landscape, success depends not just on prompting large language models but on orchestrating them into intelligent systems that are scalable, compliant, and cost-effective.
Intelligent Estimation: A Soft Computing Paradigm presents a unified treatment of a new soft computing framework using AI-based approaches for system identification, parameter estimation, and filtering.
Intelligent Estimation: A Soft Computing Paradigm presents a unified treatment of a new soft computing framework using AI-based approaches for system identification, parameter estimation, and filtering.
Introduction to Generative AI: Theoretical Foundations, Analysis and Practical Use CasesGenerative Artificial Intelligence is reshaping how we create, learn, and imagine.
Introduction to Generative AI: Theoretical Foundations, Analysis and Practical Use CasesGenerative Artificial Intelligence is reshaping how we create, learn, and imagine.
Artificial Intelligence in Tribology presents the use of machine learning, AI, neural networks, and optimization algorithms in studying friction, wear, and lubrication.
Artificial Intelligence in Tribology presents the use of machine learning, AI, neural networks, and optimization algorithms in studying friction, wear, and lubrication.
"e;Call Jotting Using 80-dim Fbank Audio Input CNN Feature Extraction Methods with RBM-DBN Pre-training HMM Temporal Smoothing and MLP Classifier AlgorithmsFunctions, Techniques, and Comparative AnalysisThis book presents a rigorous, first-principles analysis of every machine learning function, architectural component, loss criterion, and training technique used across 18 generations (V1–V18) of CallJots audio-plus-text jot extraction research — 765 experiments in total — delivering the most comprehensive comparative study of neural architectures for automatic speech jot classification ever published.
This book is about computational models of reading, or models that explain (and often simulate) the mental processes that allow us to convert the marks on a printed page into the representations that allow us to understand the contents of what we are reading.
Distributed AI in the Modern World: Technical and Social Aspects of Interacting Intelligent Agents presents state-of-the-art insights into the various forms of distribution of artificial intelligence, with practical application instances.
Solve machine learning engineering challenges for GenAI-powered systems and AI agents on AWS, and automate LLMOps pipelines using Amazon Bedrock, SageMaker AI, Bedrock AgentCore, and Strands Agents.
Solve machine learning engineering challenges for GenAI-powered systems and AI agents on AWS, and automate LLMOps pipelines using Amazon Bedrock, SageMaker AI, Bedrock AgentCore, and Strands Agents.
Reinforcement Learning (RL) is a branch of Artificial Intelligence (AI) where agents learn optimal behavior through interaction with an environment by receiving feedback in the form of reward.
Reinforcement Learning (RL) is a branch of Artificial Intelligence (AI) where agents learn optimal behavior through interaction with an environment by receiving feedback in the form of reward.
Although the use of fuzzy control methods has grown nearly to the level of classical control, the true understanding of fuzzy control lags seriously behind.
Healthcare operations, in hospitals and home healthcare settings, are inundated with complex fuzzy features that impose difficulties in the creation of work schedules.
The area of biologically inspired computing, or biological computation, involves the development of new, biologically based techniques for solving difficult computational problems.
How are cloud computing, fog computing, edge computing, and artificial intelligence (AI) working together to create intelligent mobile and IoT ecosystems?
How are cloud computing, fog computing, edge computing, and artificial intelligence (AI) working together to create intelligent mobile and IoT ecosystems?
