DESCRIPTION
Large language models (LLMs) have emerged as powerful tools in chemistry, enabling new approaches to scientifc discovery. While many chemists find these AI models interesting, they may lack a certain knowledge base to better integrate these tools into their daily research.
This book breaks down that barrier by demystifying how LLMs work in an accessible way and showing, step by step, how they can be applied to solve real chemistry problems. It begins by gently introducing artifcial intelligence and machine learning concepts in lay terms, building up to the inner workings of LLMs without heavy math. Readers will learn how these models “think” and generate text, gaining an intuitive understanding of concepts like neural networks, transformers. It spans from understanding chemical nomenclature and reactions as a “language” to exploring how an LLM can suggest synthetic routes or explain spectral data.
Beyond theory, the book emphasizes practical application. Each chapter includes hands-on tutorials and case studies that invite readers to experiment with real tools.
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