Books like Probability and statistics for computer science by Johnson, James L.

The Elements of Statistical Learning explains key statistical methods that underlie modern machine learning, data mining, and bioinformatics, covering supervised and unsupervised learning techniques such as classification trees, neural networks, and support vector machines.

A concise primer on probability theory and stochastic models for science, engineering, economics and related disciplines.

A comprehensive guide to probability theory with applications in statistics and machine learning, suitable for graduate students and professionals alike.

Computer algebra systems are now ubiquitous in all areas of science and engineering. This highly successful textbook, widely regarded as the "bible of computer algebra", gives a thorough introduction to the algorithmic basis of the mathematical engine in computer algebra systems. Designed to accompany one- or two- semester courses for advanced undergraduate or graduate students in computer science or mathematics, its comprehensiveness and reliability has also made it an essential reference for professionals in the area. Special features include: detailed study of algorithms including time analysis; implementation reports on several topics; complete proofs of the mathematical underpinnings; and a wide variety of applications (among others, in chemistry, coding theory, crytopgraphy, computational logic, and the design of calendars and musical scales). A great deal of historical information and illustration enlivens the text.