143 rezultatov
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AI for Physics(2022) KNECHT, VOLKERWritten in accessible language without mathematical formulas, the book covers important machine learning algorithms and their respective applications in physics and across a number of important sub-fields in more detail, ranging from particle, molecular aVezava: Mehka44,09 € -
Foundations of Probabilistic Programming(2020)This book provides an overview of the theoretical underpinnings of modern probabilistic programming and presents applications in e.g., machine learning, security, and approximate computing. Comprehensive survey chapters make the material accessible to graVezava: Trda94,97 € -
Essentials of Pattern Recognition(2020) WU, JIANXIN (NANJING UNIVERSITY, CHINA)Introduces fundamental concepts, major models, and popular applications of pattern recognition for a one-semester undergraduate course. The text focuses on a relatively small number of core concepts with an abundance of illustrations and examples and provVezava: Trda93,27 € -
Machine Learning in Asset Pricing(2021) NAGEL, STEFANA groundbreaking, authoritative introduction to how machine learning can be applied to asset pricingInvestors in financial markets are faced with an abundance of potentially value-relevant information from a wide variety of different sources. In such dataVezava: Trda64,88 € -
Azure AI Services at Scale for Cloud, Mobile, and Edge(2022) BISSON, SIMON,BRANSCOMBE, MARY,HODER, CHRIS,RAMAN, ANANTake advantage of the power of cloud and the latest AI techniques. Whether you're an experienced developer wanting to improve your app with AI-powered features or you want to make a business process smarter by getting AI to do some of the work, this book'Vezava: Mehka67,97 € -
Essential Math for Data Science(2022) NIELD, THOMASTo succeed in data science you need some math proficiency. But not just any math. This common-sense guide provides a clear, plain English survey of the math you'll need in data science, including probability, statistics, hypothesis testing, linear algebraVezava: Mehka67,97 € -
Scaling up Machine Learning(2018)In many practical situations it is impossible to run existing machine learning methods on a single computer, because either the data is too large or the speed and throughput requirements are too demanding. Researchers and practitioners will find here a vaVezava: Mehka76,31 € -
Introduction to Natural Language Processing(2019) EISENSTEIN, JACOB (ASSISTANT PROFESSOR, GOOGLE)Vezava: Trda103,80 € -
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Machine Learning with Neural Networks(2021) MEHLIG, BERNHARD (GOTEBORGS UNIVERSITET, SWEDEN)This modern and self-contained book offers a clear and accessible introduction to the important topic of machine learning with neural networks. Fundamental physical and mathematical principles of the topic are described alongside current applications in sVezava: Trda73,49 € -
Managing Machine Learning Projects(2023) THOMPSON, SIMONFor anyone interested in better management of machine learning projects from idea to production. Managing Machine Learning Projects is a comprehensive guide that does not require any technical skills. This edition will help you discover battle-tested dataVezava: Trda73,13 € -
Machine Learning with Python Cookbook(2023) GALLATIN, KYLE,ALBON, CHRISThis practical guide provides more than 200 self-contained recipes to help you solve machine learning challenges you may encounter in your work.Vezava: Mehka82,08 € -
Implementing MLOps in the Enterprise(2023) HAVIV, YARON,GIFT, NOAHThis practical guide helps your company bring data science to life for different real-world MLOps scenarios. Senior data scientists, MLOps engineers, and machine learning engineers will learn how to tackle challenges that prevent many businesses from moviVezava: Mehka82,08 €
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Low-Code AI(2023) STRIPLING, GWENDOLYNE,ABEL, MICHAELThis hands-on guide presents three problem-focused ways to learn ML: no code using AutoML, low-code using BigQuery ML, and custom code using scikit-learn and Keras. You'll learn key ML concepts by using real-world datasets with realistic problems.Vezava: Mehka82,08 €
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Deep Reinforcement Learning(2022) PLAAT, ASKEDeep reinforcement learning has attracted considerable attention recently. Biology has inspired the creation of artificial neural networks and deep learning, while psychology studies how animals and humans learn, and how subjects’ desired behavior can beVezava: Mehka68,68 € -
Applied Machine Learning and AI for Engineers(2022) PROSISE, JEFFWhile many introductory guides to AI are calculus books in disguise, this one mostly eschews the math. Instead, author Jeff Prosise helps engineers and software developers build an intuitive understanding of AI to solve business problems.Vezava: Mehka82,08 € -
Probabilistic Machine Learning for Finance and Investing(2023) KANUNGO, DEEPAK K.By moving away from flawed statistical methodologies, you'll move toward an intuitive view of probability as a mathematically rigorous statistical framework that quantifies uncertainty holistically and successfully. This book shows you how.Vezava: Mehka82,08 €
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Practical Simulations for Machine Learning(2022) BUTTFIELD-ADDISON, PARIS,BUTTFIELD-ADDISON, MARS,NUGENT, TIM,MANNING, JONWith this practical book, you'll explore the possibilities of simulation- and synthesis-based machine learning and AI, concentrating on deep reinforcement learning and imitation learning techniques. AI and ML are increasingly data driven, and simulationsVezava: Mehka67,97 € -
TensorFlow 2 Pocket Reference(2021) TUNG, K. C.This easy-to-use reference for Tensorflow 2 design patterns in Python will help you make informed decisions for various use cases. Author KC Tung addresses common topics and tasks in enterprise data science and machine learning practices rather than focusVezava: Mehka33,34 €
