Machine Learning: Foundations, Methodologies, and Applications - Böcker

Genetic Programming for Production Scheduling

An Evolutionary Learning Approach

Genetic Programming for Production Scheduling

An Evolutionary Learning Approach

Machine Learning

The Basics

Machine Learning

The Basics

Foundations of Deep Learning

Foundations of Deep Learning

Artificial Intelligence with Python

Evolutionary Multi-Task Optimization

Foundations and Methodologies

Evolutionary Multi-Task Optimization

Foundations and Methodologies

Concise Guide to Quantum Machine Learning

Concise Guide to Quantum Machine Learning

Federated Learning

Fundamentals and Advances

Federated Learning

Fundamentals and Advances

Introduction to Transfer Learning

Algorithms and Practice

Introduction to Transfer Learning

Algorithms and Practice

Graph Neural Network Training

From Data Management Perspective

Cross-device Federated Recommendation

Privacy-Preserving Personalization

Cross-device Federated Recommendation

Privacy-Preserving Personalization

Embodied Multi-Agent Systems

Perception, Action, and Learning

Derivative-Free Optimization

Theoretical Foundations, Algorithms, and Applications

Topic Modeling

Advanced Techniques and Applications

Machine Learning with Julia

An Algorithmic Exploration

Robust Machine Learning

Distributed Methods for Safe AI

Robust Machine Learning

Distributed Methods for Safe AI

Unsupervised Domain Adaptation

Recent Advances and Future Perspectives

Unsupervised Domain Adaptation

Recent Advances and Future Perspectives

Artificial Intelligence in Business Management

Artificial Intelligence in Business Management

Online Machine Learning

A Practical Guide with Examples in Python