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  • Book

  • Competitive Programming 4 - Book 2 : The Lower Bound of Programming Contests in the 2020s

    • Authors: Steven Halim (2020)

  • This Competitive Programming book, 4th edition (CP4) is a must have for every competitive programmer. Mastering the contents of this book is a necessary (but admittedly not sufficient) condition if one wishes to take a leap forward from being just another ordinary coder to being among one of the world's finest competitive programmers.
  • Book

  • Competitive Programming 4 - Book 1 : The Lower Bound of Programming Contests in the 2020s

    • Authors: Steven Halim (2020)

  • This Competitive Programming book, 4th edition (CP4) is a must have for every competitive programmer. Mastering the contents of this book is a necessary (but admittedly not sufficient) condition if one wishes to take a leap forward from being just another ordinary coder to being among one of the world's finest competitive programmers.
  • Book

  • Computer Network Security

    • Authors: Ali Sadiqui (2020)

  • Computer Network Security is an exploration of the state-of-the-art and good practices in setting up a secure computer system. Concrete examples are offered in each chapter, to help the reader to master the concept and apply the security configuration.
  • Sách/Book

  • Computer Security and the Internet : Tools and Jewels

    • Authors: Paul C. van Oorschot (2020)

  • This book provides a concise yet comprehensive overview of computer and Internet security, suitable for a one-term introductory course for junior/senior undergrad or first-year graduate students.
  • Sách/Book

  • Convex Analysis for Optimization (Graduate Texts in Operations Research)

    • Authors: Jan Brinkhuis (2020)

  • The book introduces a systematic three-step method for doing everything, which can be summarized as "conify, work, deconify". It starts with the concept of convex sets, their primal description, constructions, topological properties and dual description, and then moves on to convex functions and the fundamental principles of convex optimization and their use in the complete analysis of convex optimization problems by means of a systematic four-step method.
  • Sách/Book

  • Foundations of data science

    • Authors: Avrim Blum (2020)

  • This book provides an introduction to the mathematical and algorithmic foundations of data science, including machine learning, high-dimensional geometry, and analysis of large networks. Topics include the counterintuitive nature of data in high dimensions, important linear algebraic techniques such as singular value decomposition, the theory of random walks and Markov chains, the fundamentals of and important algorithms for machine learning, algorithms and analysis for clustering, probabilistic models for large networks, representation learning including topic modelling and non-negative matrix factorization, wavelets and compressed sensing
  • Sách/Book

  • Data Science for Business and Decision Making : An Introductory Text for Students and Practitioners

    • Authors: Seyed Ali Fallahchay (2020)

  • This book explores the principles underpinning data science. It considers the how and why of modern data science. The book goes further than existing books by applying data to decision making. Not only is the book useful for undergraduates, but it can also help business owners in improving their decision making. Using real life examples, this book explores the possibilities and limitations of an information-based decision making framework.