Algorithms and data structures

This book presents state-of-the-art technical contributions based around one of the most successful evolutionary optimization algorithms published to date: Harmony Search.

Modern computing tools like Maple (symbolic computation) and Matlab (a numeric computation and visualization program) make it possible to easily solve realistic nontrivial problems in scientific computing.

Robust control mechanisms customarily require knowledge of the system's describing equations which may be of the high order differential type.

Biomolecular sequence comparison is the origin of bioinformatics.

Often, real-world problems modeled by Markov decision processes (MDPs) are difficult to solve in practise because of the curse of dimensionality.

Most data compression methods that are based on variable-length codes employ the Huffman or Golomb codes.

Noisy data appear very naturally in applications where the authentication is based on physical identifiers.

An accessible introduction to the fundamental algorithms used to run the world.

The beating heart of any product or service business is returning clients.

Markov decision process (MDP) models are widely used for modeling sequential decision-making problems that arise in engineering, economics, computer science, and the social sciences.

The recent explosive growth of our ability to generate and store data has created a need for new, scalable and efficient, tools for data analysis.

Learn statistics by analyzing professional basketball data!

Grokking Deep Reinforcement Learning uses engaging exercises to teach you how to build deep learning systems.

Sharpen your coding skills by exploring established computer science problems!

Summary Companies small and large are initiating AI projects, investing vast sums of money on software, developers, and data scientists.

From start to finish, the best book to help you learn AI algorithms and recall why and how you use them.

SummaryAlgorithms of the Intelligent Web, Second Edition teaches the most important approaches to algorithmic web data analysis, enabling you to create your own machine learning applications that crunch, munge, and wrangle data collected from users, web applications, sensors and website logs.

SummarySpark in Action teaches you the theory and skills you need to effectively handle batch and streaming data using Spark.

Updated with new code, new projects, and new chapters, Machine Learning with TensorFlow, Second Edition gives readers a solid foundation in machine-learning concepts and the TensorFlow library.

This book does the impossible: it makes math fun and easy!

SummaryGenerative Art presents both the technique and the beauty of algorithmic art.

SummaryPractical Probabilistic Programming introduces the working programmer to probabilistic programming.

SummaryThink Like a Data Scientist presents a step-by-step approach to data science, combining analytic, programming, and business perspectives into easy-to-digest techniques and thought processes for solving real world data-centric problems.

SummaryMahout in Action is a hands-on introduction to machine learning with Apache Mahout.

This book presents state-of-the-art technical contributions based around one of the most successful evolutionary optimization algorithms published to date: Harmony Search.

Concurrency doesn't need to be confusing.

Learn about quantum information processing with Qiskit through hands-on projects.

Este libro es la guía definitiva para dominar Excel y Power BI, dos de las herramientas más poderosas en el mundo del análisis y visualización de datos.

This book offers a thorough overview of permissioned blockchain systems, emphasizing how they can tackle key challenges in large-scale transaction management systems.

This book offers a thorough overview of permissioned blockchain systems, emphasizing how they can tackle key challenges in large-scale transaction management systems.

Esta cartilla pretende ser una motivacion para profundizar en el analisis de situaciones problema utilizando el lenguaje de programacion R dado que es una herramienta muy versatil que cuenta con un software libre y esta en constante actualizacion.

Iterative algorithms often rely on approximate evaluation techniques, which may include statistical estimation, computer simulation or functional approximation.

Integer Programming: Theory and Practice contains refereed articles that explore both theoretical aspects of integer programming as well as major applications.