Graph Transformation: 12th International Conference, ICGT 2019, Held as Part of STAF 2019, Eindhoven, The Netherlands, July 15–16, 2019, Proceedings

AI Engineering: Building Applications with Foundation Models

Formal Methods for Industrial Critical Systems: 17th International Workshop, FMICS 2012, Paris, France, August 27-28, 2012, Proceedings

Sound Systems: Design and Optimization: Modern Techniques and Tools for Sound System Design and Alignment, Edition 3

Transformers for Natural Language Processing: Build innovative deep neural network architectures for NLP with Python, PyTorch, TensorFlow, BERT, RoBERTa, and more

Theory and Practice of Model Transformation: 10th International Conference, ICMT 2017, Held as Part of STAF 2017, Marburg, Germany, July 17-18, 2017, Proceedings

Prompt Engineering - The Ultimate Guide for Success in Artificial Intelligence

Stochastic Model Checking: International Autumn School, ROCKS 2012, Vahrn, Italy, October 22-26, 2012. Advanced Lectures

LLM Engineer's Handbook: Master the art of engineering large language models from concept to production

Formal Modeling and Analysis of Timed Systems: 17th International Conference, FORMATS 2019, Amsterdam, The Netherlands, August 27–29, 2019, Proceedings

Decoding the Universe: How the New Science of Information Is Explaining Everythingin the Cosmos, fromOur Brains to Black Holes

A Journey from Process Algebra via Timed Automata to Model Learning: Essays Dedicated to Frits Vaandrager on the Occasion of His 60th Birthday

Organic Intelligence (O.I.): Why Humans Will Always Beat A.I.

Quantitative Evaluation of Systems: 10th International Conference, QEST 2013, Buenos Aires, Argentina, August 27-30, 2013, Proceedings

Audio Engineering - Dynamic Processing

From ML Algorithms to GenAI & LLMs: Master ML Algorithms and Generative AI & LLMs with Python from scratch!

Principles of Verification: Cycling the Probabilistic Landscape: Essays Dedicated to Joost-Pieter Katoen on the Occasion of His 60th Birthday, Part III

Logic Pro X: Audio and Music Production

Introduction to Machine Learning with Python: A Guide for Data Scientists