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Computer Science & Engineering Collections de eBooks

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  • Distributed Simulation

    par John A. Hamilton, David A. Nash, Udo W. Pooch ...
    Collection series Computer Science & Engineering
    Simulation is a multi-disciplinary field, and significant simulation research is dispersed across multiple fields of study. Distributed computer systems, software design methods, and new simulation techniques offer synergistic multipliers when joined together in a distributed simulation. Systems of most interest to the simulation practitioner are often the most difficult to model and implement. ... En savoir plus

    CHF 110.62

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  • Data Mining

    Practical Machine Learning Tools and Techniques

    par Eibe Frank, Mark A. Hall, Ian H. Witten ...
    Data Mining: Practical Machine Learning Tools and Techniques, Third Edition, offers a thorough grounding in machine learning concepts as well as practical advice on applying machine learning tools and techniques in real-world data mining situations. This highly anticipated third edition of the most acclaimed work on data mining and machine learning will teach you everything you need to know about ... En savoir plus

    CHF 52.01

  • Machine Learning with R

    R gives you access to the cutting-edge software you need to prepare data for machine learning. No previous knowledge required – this book will take you methodically through every stage of applying machine learning.

    par Brett Lantz ...
    Written as a tutorial to explore and understand the power of R for machine learning. This practical guide that covers all of the need to know topics in a very systematic way. For each machine learning approach, each step in the process is detailed, from preparing the data for analysis to evaluating the results. These steps will build the knowledge you need to apply them to your own data science ... En savoir plus

    CHF 43.39 ou Gratuit avec Kobo Plus

  • Data Mining: Concepts and Techniques

    par Jiawei Han, Micheline Kamber, Jian Pei ...
    Collection series The Morgan Kaufmann Series in Data Management Systems
    Data Mining: Concepts and Techniques provides the concepts and techniques in processing gathered data or information, which will be used in various applications. Specifically, it explains data mining and the tools used in discovering knowledge from the collected data. This book is referred as the knowledge discovery from data (KDD). It focuses on the feasibility, usefulness, effectiveness, and ... En savoir plus

    CHF 55.70

  • Machine Learning with R

    Expert techniques for predictive modeling to solve all your data analysis problems

    par Brett Lantz ...
    Key FeaturesBook DescriptionUpdated and upgraded to the latest libraries and most modern thinking, Machine Learning with R, Second Edition provides you with a rigorous introduction to this essential skill of professional data science. Without shying away from technical theory, it is written to provide focused and practical knowledge to get you building algorithms and crunching your data, with ... En savoir plus

    CHF 39.70 ou Gratuit avec Kobo Plus

  • Data Mining

    Practical Machine Learning Tools and Techniques, Second Edition

    par Eibe Frank, Ian H. Witten ...
    Collection series The Morgan Kaufmann Series in Data Management Systems
    Data Mining, Second Edition, describes data mining techniques and shows how they work. The book is a major revision of the first edition that appeared in 1999. While the basic core remains the same, it has been updated to reflect the changes that have taken place over five years, and now has nearly double the references. The highlights of this new edition include thirty new technique sections; an ... En savoir plus

    Avant CHF 59.70 Après CHF 53.14

  • Machine Learning Algorithms

    A reference guide to popular algorithms for data science and machine learning

    par Giuseppe Bonaccorso ...
    Build strong foundation for entering the world of Machine Learning and data science with the help of this comprehensive guideKey Features\[\*\] Get started in the field of Machine Learning with the help of this solid, concept-rich, yet highly practical guide.\[\*\] Your one-stop solution for everything that matters in mastering the whats and whys of Machine Learning algorithms and their ... En savoir plus

    CHF 39.70 ou Gratuit avec Kobo Plus

  • Machine Learning with R

    Expert techniques for predictive modeling

    par Brett Lantz ...
    Solve real-world data problems with R and machine learningKey FeaturesThird edition of the bestselling, widely acclaimed R machine learning book, updated and improved for R 3.6 and beyondHarness the power of R to build flexible, effective, and transparent machine learning modelsLearn quickly with a clear, hands-on guide by experienced machine learning teacher and practitioner, Brett LantzBook ... En savoir plus

    CHF 42.47 ou Gratuit avec Kobo Plus

  • TensorFlow for Deep Learning

    From Linear Regression to Reinforcement Learning

    par Bharath Ramsundar, Reza Bosagh Zadeh ...
    Learn how to solve challenging machine learning problems with TensorFlow, Google’s revolutionary new software library for deep learning. If you have some background in basic linear algebra and calculus, this practical book introduces machine-learning fundamentals by showing you how to design systems capable of detecting objects in images, understanding text, analyzing video, and predicting the ... En savoir plus

    CHF 34.16

  • Python: Advanced Predictive Analytics

    Gain practical insights by exploiting data in your business to build advanced predictive modeling applications

    par Ashish Kumar, Joseph Babcock ...
    Gain practical insights by exploiting data in your business to build advanced predictive modeling applicationsKey FeaturesA step-by-step guide to predictive modeling including lots of tips, tricks, and best practicesLearn how to use popular predictive modeling algorithms such as Linear Regression, Decision Trees, Logistic Regression, and ClusteringMaster open source Python tools to build ... En savoir plus

    CHF 56.93 ou Gratuit avec Kobo Plus

  • Thoughtful Machine Learning

    A Test-Driven Approach

    par Matthew Kirk ...
    Learn how to apply test-driven development (TDD) to machine-learning algorithms—and catch mistakes that could sink your analysis. In this practical guide, author Matthew Kirk takes you through the principles of TDD and machine learning, and shows you how to apply TDD to several machine-learning algorithms, including Naive Bayesian classifiers and Neural Networks.Machine-learning algorithms often ... En savoir plus

    CHF 14.87

  • Deep Learning with R for Beginners

    Design neural network models in R 3.5 using TensorFlow, Keras, and MXNet

    par Mark Hodnett, Joshua F. Wiley, Yuxi (Hayden) Liu, Pablo Maldonado ...
    Explore the world of neural networks by building powerful deep learning models using the R ecosystemKey FeaturesGet to grips with the fundamentals of deep learning and neural networksUse R 3.5 and its libraries and APIs to build deep learning models for computer vision and text processingImplement effective deep learning systems in R with the help of end-to-end projectsBook DescriptionDeep ... En savoir plus

    CHF 24.92 ou Gratuit avec Kobo Plus