Christopher J Pallister Books

This fourth edition offers a comprehensive grounding in machine learning concepts and practical advice for real-world data mining applications. It covers everything from input preparation and output interpretation to evaluating results and the algorithmic methods central to successful data mining. The edition includes extensive updates reflecting recent technical advancements, with new chapters dedicated to probabilistic methods and deep learning. Additionally, it features a new version of the popular WEKA machine learning software from the University of Waikato. The authors, Witten, Frank, Hall, and Pal, integrate contemporary techniques with cutting-edge research methods. A companion website provides PowerPoint slides for Chapters 1-12, serving as a valuable teaching resource. The online appendix focuses on the Weka workbench, offering extensive learning aids for the accompanying open-source software. The table of contents highlights the new sections in this edition, along with reviews of the first edition and errata, ensuring a thorough educational experience for readers.

Haematology is a rapidly changing subject, and it is therefore difficult for students of medicine, veterinary science or biomedical sciences to attain the level of knowledge required to get the most from their studies and interpret and learn from scientific papers in the subject. This book is intended to bridge the gap between what students already know and the latest cutting edge advances in the subject. As such, it is aimed primarily at final year undergraduate students and those embarking on postgraduate qualifications, as well as trainee laboratory staff.