Timeless Algorithms: The Seminal Papers

Gary Sutton is a leader in business intelligence and analytics. He is known for making complex statistical ideas easy to understand. With his experience in the field, he brings a practical and clear voice to his writing. Gary Sutton helps readers connect timeless theories to the real-world challenges of building modern AI systems.

• 1 SEEING INSIDE THE BLACK BOX 2 FROM EFFECT TO CAUSE: BAYES' THEOREM AND THE FIRST ALGORITHM OF LEARNING 3 THE ALGORITHM OF ESTIMATION: RONALD FISHER'S LIKELIHOOD PRINCIPLE 4 TESTING WHAT WE ASSUME TO KNOW: NEYMAN, PEARSON, AND THE PRINCIPLES OF HYPOTHESIS TESTING 5 THE BIRTH OF INFORMATION THEORY: SHANNON AND THE MATHEMATICS OF UNCERTAINTY 6 THE LOGIC OF MULTI-STAGE DECISION PROCESSES: RICHARD BELLMAN AND THE PRINCIPLE OF RECURSIVE OPTIMIZATION 7 FROM INFERENCE TO CHOICE: HOWARD RAIFFA, ROBERT SCHLAIFER, AND THE BAYESIAN REVOLUTION 8 THE GEOMETRY OF SEPARATION: VLADIMIR VAPNIK AND THE MATHEMATICS OF SUPPORT VECTOR MACHINES 9 FROM SINGLE TREES TO FORESTS: LEO BREIMAN AND THE LOGIC OF ENSEMBLE LEARNING 10 FROM ISOLATED ALGORITHMS TO COHERENT SYSTEMS: DAVID J.C. MACKAY AND THE UNIFYING LOGIC OF LEARNING 11 LEARNING THROUGH REPRESENTATION: LECUN, BENGIO, HINTON, AND THE MATHEMATICS OF NEURAL NETWORKS 12 FROM RECURRENCE TO ATTENTION: GOOGLE BRAIN AND THE TRANSFORMER ARCHITECTURE  13 FROM FOUNDATIONS TO FRONTIER: OPEN AI AND THE SCALING LAWS OF MODERN INTELLIGENCE