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Auteur Giuseppe CIABURRO |
Documents disponibles écrits par cet auteur (4)
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Hands-On Simulation Modeling with Python : Develop simulation models for improved efficiency and precision in the decision-making process / Giuseppe CIABURRO / PACKT PUBLISHING (2022)
Titre : Hands-On Simulation Modeling with Python : Develop simulation models for improved efficiency and precision in the decision-making process Type de document : e-book Auteurs : Giuseppe CIABURRO Editeur : PACKT PUBLISHING Année de publication : 2022 ISBN/ISSN/EAN : 9781804616888 Note générale : copyrighted Langues : Anglais (eng) Résumé : Learn to construct state-of-the-art simulation models with Python and enhance your simulation modelling skills, as well as create and analyze digital prototypes of physical models with easeKey FeaturesUnderstand various statistical and physical simulations to improve systems using PythonLearn to create the numerical prototype of a real model using hands-on examplesEvaluate performance and output results based on how the prototype would work in the real worldBook DescriptionSimulation modelling is an exploration method that aims to imitate physical systems in a virtual environment and retrieve useful statistical inferences from it. The ability to analyze the model as it runs sets simulation modelling apart from other methods used in conventional analyses. This book is your comprehensive and hands-on guide to understanding various computational statistical simulations using Python. The book begins by helping you get familiarized with the fundamental concepts of simulation modelling, that'll enable you to understand the various methods and techniques needed to explore complex topics. Data scientists working with simulation models will be able to put their knowledge to work with this practical guide. As you advance, you'll dive deep into numerical simulation algorithms, including an overview of relevant applications, with the help of real-world use cases and practical examples. You'll also find out how to use Python to develop simulation models and how to use several Python packages. Finally, you'll get to grips with various numerical simulation algorithms and concepts, such as Markov Decision Processes, Monte Carlo methods, and bootstrapping techniques.By the end of this book, you'll have learned how to construct and deploy simulation models of your own to overcome real-world challenges.What you will learnGet to grips with the concept of randomness and the data generation processDelve into resampling methodsDiscover how to work with Monte Carlo simulationsUtilize simulations to improve or optimize systemsFind out how to run efficient simulations to analyze real-world systemsUnderstand how to simulate random walks using Markov chainsWho this book is forThis book is for data scientists, simulation engineers, and anyone who is already familiar with the basic computational methods and wants to implement various simulation techniques such as Monte-Carlo methods and statistical simulation using Python. Nombre d'accès : Illimité En ligne : http://library.ez.neoma-bs.fr/login?url=https://www.scholarvox.com/book/88938074 Permalink : https://cataloguelibrary.neoma-bs.fr/index.php?lvl=notice_display&id=563429
Titre : Python Machine Learning Cookbook - Second Edition Type de document : e-book Auteurs : Giuseppe CIABURRO Editeur : PACKT PUBLISHING Année de publication : 2019 ISBN/ISSN/EAN : 9781789808452 Note générale : copyrighted Langues : Anglais (eng) Résumé : Discover powerful ways to effectively solve real-world machine learning problems using key libraries including scikit-learn, TensorFlow, and PyTorch Key Features Learn and implement machine learning algorithms in a variety of real-life scenarios Cover a range of tasks catering to supervised, unsupervised and reinforcement learning techniques Find easy-to-follow code solutions for tackling common and not-so-common challenges Book Description This eagerly anticipated second edition of the popular Python Machine Learning Cookbook will enable you to adopt a fresh approach to dealing with real-world machine learning and deep learning tasks. With the help of over 100 recipes, you will learn to build powerful machine learning applications using modern libraries from the Python ecosystem. The book will also guide you on how to implement various machine learning algorithms for classification, clustering, and recommendation engines, using a recipe-based approach. With emphasis on practical solutions, dedicated sections in the book will help you to apply supervised and unsupervised learning techniques to real-world problems. Toward the concluding chapters, you will get to grips with recipes that teach you advanced techniques including reinforcement learning, deep neural networks, and automated machine learning. By the end of this book, you will be equipped with the skills you need to apply machine learning techniques and leverage the full capabilities of the Python ecosystem through real-world examples. What you will learn Use predictive modeling and apply it to real-world problems Explore data visualization techniques to interact with your data Learn how to build a recommendation engine Understand how to interact with text data and build models to analyze it Work with speech data and recognize spoken words using Hidden Markov Models Get well versed with reinforcement learning, automated ML, and transfer learning Work with image data and build systems for image recognition and biometric face recognition Use deep neural networks to build an optical character recognition system Who this book is for This book is for data scientists, machine learning developers, deep learning enthusiasts and Python programmers who want to solve real-world challenges using machine-learning techniques and algorithms. If you are facing challenges at work and want ready-to-use code solutions to cover key tasks in machine learning and the deep learning domain, then this book is what you need. Familiarity with Python programming and machine learning concepts will be useful. Nombre d'accès : Illimité En ligne : http://library.ez.neoma-bs.fr/login?url=https://www.scholarvox.com/book/88867576 Permalink : https://cataloguelibrary.neoma-bs.fr/index.php?lvl=notice_display&id=484866
Titre : Hands-On Machine Learning on Google Cloud Platform Type de document : e-book Auteurs : Giuseppe CIABURRO Editeur : PACKT PUBLISHING Année de publication : 2018 ISBN/ISSN/EAN : 9781788393485 Note générale : copyrighted Langues : Anglais (eng) Nombre d'accès : Illimité En ligne : http://library.ez.neoma-bs.fr/login?url=https://www.scholarvox.com/book/88856876 Permalink : https://cataloguelibrary.neoma-bs.fr/index.php?lvl=notice_display&id=481241
Titre : Keras Reinforcement Learning Projects Type de document : e-book Auteurs : Giuseppe CIABURRO Editeur : PACKT PUBLISHING Année de publication : 2018 ISBN/ISSN/EAN : 9781789342093 Note générale : copyrighted Langues : Anglais (eng) Nombre d'accès : Illimité En ligne : http://library.ez.neoma-bs.fr/login?url=https://www.scholarvox.com/book/88863286 Permalink : https://cataloguelibrary.neoma-bs.fr/index.php?lvl=notice_display&id=483366
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