Data Science & AI Books

This educational guide will help students and practitioners seeking to understand the fundamentals and practice of linear programming. The exercises contained within demonstrate how to solve classical optimization problems with an emphasis on spatial analysis in supply chain management and transport logistics. All exercises describe the Python prog

Games have long been excellent benchmarks for AI algorithms for two reasons. Initially, games are developed to assess and challenge human intelligence, and the variety of games can provide a rich context for evaluating different cognitive and decision-making abilities. Secondly, addressing complex real-world challenges often requires repeated trial

Data science is the process of representing models that fit data. Its goal is to predict future output based on past observations of inputs. In data science, one collects information and interprets it to make decisions. This open book contains two parts, the first is designed to be used in an introductory programming course for students looking to

The Shallow and the Deep is a collection of lecture notes that offers an accessible introduction to neural networks and machine learning in general. However, it was clear from the beginning that these notes would not be able to cover this rapidly changing and growing field in its entirety. The focus lies on classical machine learning techniques, wi

As the software development landscape evolves, the challenge of managing and refactoring extensive code bases becomes increasingly complex. AI methods of code refactoring, while effective for smaller scales, can falter under the weight of mass-scale operations. The need for efficiency, accuracy, and consistency is more critical than ever. This key

Principles of Data Science is intended to support one- or two-semester courses in data science. It is appropriate for data science majors and minors as well as students concentrating in business, finance, health care, engineering, the sciences, and a number of other fields where data science has become critically important. The authors have include

Introduction to Computer Science provides a comprehensive foundation in core computer science concepts and principles, aligning with the scope and sequence of most introductory computer science courses. The offering serves as an engaging entry point for students pursuing diverse fields of study and employment, including computer science, business,

OpenIntro Statistics provides a traditional college-level introduction to the field of statistics. This widely adopted textbook offers an exceptional and accessible foundation for a diverse range of students, from those at community colleges to attendees of Ivy League institutions. It is estimated that approximately 20,000 students use this thoroug

Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives while interacting with a complex, uncertain environment. In Reinforcement Learning, Richard Sutton and Andrew Barto provide a clear and simple acc

Inventory Analytics provides a comprehensive and accessible introduction to the theory and practice of inventory control - a significant research area central to supply chain planning. The book outlines the foundations of inventory systems and surveys prescriptive analytics models for deterministic inventory control. It further discusses predictive