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Ajouter au panierEtat : New. Brand New. Soft Cover International Edition. Different ISBN and Cover Image. Priced lower than the standard editions which is usually intended to make them more affordable for students abroad. The core content of the book is generally the same as the standard edition. The country selling restrictions may be printed on the book but is no problem for the self-use. This Item maybe shipped from US or any other country as we have multiple locations worldwide.
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Ajouter au panierEtat : New. Brand New, Softcover edition. This item may ship from the US or our Overseas warehouse depending on your location and stock availability.
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Ajouter au panierEtat : New. TensorFlow Deep Learning Projects: 10 real-world projects on computer vision, machine translation, chatbots, and reinforcement learning (Paperback or Softback) 1.22.
Edité par Packt Publishing, 2018
Langue: anglais
Vendeur : Books in my Basket, New Delhi, Inde
EUR 36,13
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Ajouter au panierSoft cover. Etat : New. ISBN:9781788398060,Territorial restriction maybe printed on the book. This is an Int'l edition, ISBN and cover may differ from US edition, Contents same as US edition.
Edité par Manning Publications, US, 2021
ISBN 10 : 1617296813 ISBN 13 : 9781617296819
Langue: anglais
Vendeur : Rarewaves USA, OSWEGO, IL, Etats-Unis
EUR 51,38
Autre deviseQuantité disponible : 10 disponible(s)
Ajouter au panierPaperback. Etat : New. The only way to learn is to practice! In Machine Learning Bookcamp, you'll create and deploy Python-based machine learning models for a variety of increasingly challenging projects. Taking you from the basics of machine learning to complex applications such as image and text analysis, each new project builds on what you've learned in previous chapters. By the end of the bookcamp, you'll have built a portfolio of business-relevant machine learning projects that hiring managers will be excited to see. about the technologyMachine learning is an analysis technique for predicting trends and relationships based on historical data. As ML has matured as a discipline, an established set of algorithms has emerged for tackling a wide range of analysis tasks in business and research. By practicing the most important algorithms and techniques, you can quickly gain a footing in this important area. Luckily, that's exactly what you'll be doing in Machine Learning Bookcamp. about the bookIn Machine Learning Bookcamp you'll learn the essentials of machine learning by completing a carefully designed set of real-world projects. Beginning as a novice, you'll start with the basic concepts of ML before tackling your first challenge: creating a car price predictor using linear regression algorithms. You'll then advance through increasingly difficult projects, developing your skills to build a churn prediction application, a flight delay calculator, an image classifier, and more. When you're done working through these fun and informative projects, you'll have a comprehensive machine learning skill set you can apply to practical on-the-job problems. what's inside Code fundamental ML algorithms from scratchCollect and clean data for training modelsUse popular Python tools, including NumPy, Pandas, Scikit-Learn, and TensorFlowApply ML to complex datasets with images and textDeploy ML models to a production-ready environment about the readerFor readers with existing programming skills. No previous machine learning experience required. about the author Alexey Grigorev has more than ten years of experience as a software engineer, and has spent the last six years focused on machine learning. Currently, he works as a lead data scientist at the OLX Group, where he deals with content moderation and image models. He is the author of two other books on using Java for data science and TensorFlow for deep learning.
Edité par Manning Publications, US, 2021
ISBN 10 : 1617296813 ISBN 13 : 9781617296819
Langue: anglais
Vendeur : Rarewaves USA United, OSWEGO, IL, Etats-Unis
EUR 53,26
Autre deviseQuantité disponible : 10 disponible(s)
Ajouter au panierPaperback. Etat : New. The only way to learn is to practice! In Machine Learning Bookcamp, you'll create and deploy Python-based machine learning models for a variety of increasingly challenging projects. Taking you from the basics of machine learning to complex applications such as image and text analysis, each new project builds on what you've learned in previous chapters. By the end of the bookcamp, you'll have built a portfolio of business-relevant machine learning projects that hiring managers will be excited to see. about the technologyMachine learning is an analysis technique for predicting trends and relationships based on historical data. As ML has matured as a discipline, an established set of algorithms has emerged for tackling a wide range of analysis tasks in business and research. By practicing the most important algorithms and techniques, you can quickly gain a footing in this important area. Luckily, that's exactly what you'll be doing in Machine Learning Bookcamp. about the bookIn Machine Learning Bookcamp you'll learn the essentials of machine learning by completing a carefully designed set of real-world projects. Beginning as a novice, you'll start with the basic concepts of ML before tackling your first challenge: creating a car price predictor using linear regression algorithms. You'll then advance through increasingly difficult projects, developing your skills to build a churn prediction application, a flight delay calculator, an image classifier, and more. When you're done working through these fun and informative projects, you'll have a comprehensive machine learning skill set you can apply to practical on-the-job problems. what's inside Code fundamental ML algorithms from scratchCollect and clean data for training modelsUse popular Python tools, including NumPy, Pandas, Scikit-Learn, and TensorFlowApply ML to complex datasets with images and textDeploy ML models to a production-ready environment about the readerFor readers with existing programming skills. No previous machine learning experience required. about the author Alexey Grigorev has more than ten years of experience as a software engineer, and has spent the last six years focused on machine learning. Currently, he works as a lead data scientist at the OLX Group, where he deals with content moderation and image models. He is the author of two other books on using Java for data science and TensorFlow for deep learning.
Vendeur : Ria Christie Collections, Uxbridge, Royaume-Uni
EUR 52,21
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Ajouter au panierEtat : New. In.
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Edité par Packt Publishing 2017-04-27, 2017
ISBN 10 : 1782174273 ISBN 13 : 9781782174271
Langue: anglais
Vendeur : Chiron Media, Wallingford, Royaume-Uni
EUR 50,57
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EUR 55,76
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Vendeur : ALLBOOKS1, Direk, SA, Australie
EUR 64,86
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Ajouter au panierBrand new book. Fast ship. Please provide full street address as we are not able to ship to P O box address.
Vendeur : Majestic Books, Hounslow, Royaume-Uni
EUR 54,91
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Edité par Packt Publishing 2017-04-27, 2017
ISBN 10 : 1782174273 ISBN 13 : 9781782174271
Langue: anglais
Vendeur : Chiron Media, Wallingford, Royaume-Uni
EUR 54,55
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Ajouter au panierPaperback. Etat : New.
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EUR 49,06
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Ajouter au panierEtat : New.
Edité par Packt Publishing Limited, 2023
ISBN 10 : 1782174273 ISBN 13 : 9781782174271
Langue: anglais
Vendeur : PBShop.store UK, Fairford, GLOS, Royaume-Uni
EUR 62,25
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Ajouter au panierUNK. Etat : New. New Book. Shipped from UK. Established seller since 2000.
Edité par Packt Publishing Limited, 2023
ISBN 10 : 1782174273 ISBN 13 : 9781782174271
Langue: anglais
Vendeur : PBShop.store US, Wood Dale, IL, Etats-Unis
EUR 68,72
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Ajouter au panierUNK. Etat : New. New Book. Shipped from UK. Established seller since 2000.
Vendeur : Best Price, Torrance, CA, Etats-Unis
EUR 42,96
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Edition originale
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EUR 55,88
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Edité par Packt Publishing Limited, GB, 2023
ISBN 10 : 1782174273 ISBN 13 : 9781782174271
Langue: anglais
Vendeur : Rarewaves.com UK, London, Royaume-Uni
EUR 72,17
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Ajouter au panierDigital. Etat : New. Use Java to create a diverse range of Data Science applications and bring Data Science into productionAbout This Book. An overview of modern Data Science and Machine Learning libraries available in Java. Coverage of a broad set of topics, going from the basics of Machine Learning to Deep Learning and Big Data frameworks. Easy-to-follow illustrations and the running example of building a search engine.Who This Book Is ForThis book is intended for software engineers who are comfortable with developing Java applications and are familiar with the basic concepts of data science. Additionally, it will also be useful for data scientists who do not yet know Java but want or need to learn it.If you are willing to build efficient data science applications and bring them in the enterprise environment without changing the existing stack, this book is for you!What You Will Learn. Get a solid understanding of the data processing toolbox available in Java. Explore the data science ecosystem available in Java. Find out how to approach different machine learning problems with Java. Process unstructured information such as natural language text or images. Create your own search engine. Get state-of-the-art performance with XGBoost. Learn how to build deep neural networks with DeepLearning4j. Build applications that scale and process large amounts of data. Deploy data science models to production and evaluate their performanceIn DetailJava is the most popular programming language, according to the TIOBE index, and it is a typical choice for running production systems in many companies, both in the startup world and among large enterprises.Not surprisingly, it is also a common choice for creating data science applications: it is fast and has a great set of data processing tools, both built-in and external. What is more, choosing Java for data science allows you to easily integrate solutions with existing software, and bring data science into production with less effort.This book will teach you how to create data science applications with Java. First, we will revise the most important things when starting a data science application, and then brush up the basics of Java and machine learning before diving into more advanced topics. We start by going over the existing libraries for data processing and libraries with machine learning algorithms. After that, we cover topics such as classification and regression, dimensionality reduction and clustering, information retrieval and natural language processing, and deep learning and big data.Finally, we finish the book by talking about the ways to deploy the model and evaluate it in production settings.Style and approachThis is a practical guide where all the important concepts such as classification, regression, and dimensionality reduction are explained with the help of examples.
EUR 63,07
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