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Quantum Phase Transitions in Cold Atoms and Low Temperature Solids
The primary focus of this thesis is to theoretically describe nanokelvin experiments in cold atomic gases, which offer the potential to revolutionize our understanding of strongly correlated many-body systems. The thesis attacks major challenges of the field: it proposes and analyzes experimental protocols to create new and interesting states of matter and introduces theoretical techniques to describe probes of these states. The phenomena considered include the fractional quantum Hall effect, spectroscopy of strongly correlated states, and quantum criticality, among others. The thesis also clarifies experiments on disordered quantum solids, which display a variety of exotic phenomena and are candidates to exhibit so-called "supersolidity." It collects experimental results and constrains their interpretation through theoretical considerations. This Doctoral Thesis has been accepted by Cornell University, Ithaca, USA.
AWS Certified Machine Learning Study Guide
Succeed on the AWS Machine Learning exam or in your next job as a machine learning specialist on the AWS Cloud platform with this hands-on guide As the most popular cloud service in the world today, Amazon Web Services offers a wide range of opportunities for those interested in the development and deployment of artificial intelligence and machine learning business solutions. The AWS Certified Machine Learning Study Guide: Specialty (MLS-CO1) Exam delivers hyper-focused, authoritative instruction for anyone considering the pursuit of the prestigious Amazon Web Services Machine Learning certification or a new career as a machine learning specialist working within the AWS architecture. From ex...
Data Science on AWS
With this practical book, AI and machine learning practitioners will learn how to successfully build and deploy data science projects on Amazon Web Services. The Amazon AI and machine learning stack unifies data science, data engineering, and application development to help level upyour skills. This guide shows you how to build and run pipelines in the cloud, then integrate the results into applications in minutes instead of days. Throughout the book, authors Chris Fregly and Antje Barth demonstrate how to reduce cost and improve performance. Apply the Amazon AI and ML stack to real-world use cases for natural language processing, computer vision, fraud detection, conversational devices, and...
Data Science mit AWS
Von der ersten Idee bis zur konkreten Anwendung: Ihre Data-Science-Projekte in der AWS-Cloud realisieren Der US-Besteller zu Amazon Web Services jetzt auf Deutsch Beschreibt alle wichtigen Konzepte und die wichtigsten AWS-Dienste mit vielen Beispielen aus der Praxis Deckt den kompletten End-to-End-Prozess von der Entwicklung der Modelle bis zum ihrem konkreten Einsatz ab Mit Best Practices für alle Aspekte der Modellerstellung einschließlich Training, Deployment, Sicherheit und MLOps Mit diesem Buch lernen Machine-Learning- und KI-Praktiker, wie sie erfolgreich Data-Science-Projekte mit Amazon Web Services erstellen und in den produktiven Einsatz bringen. Es bietet einen detaillierten Einb...
AWS 기반 데이터 과학
80여 가지 AWS AI & ML 서비스로 구현하는 데이터 과학 프로젝트 실전 가이드 이 책은 AWS에서 제공하는 AI와 ML 기능을 활용하여 데이터 과학 프로젝트를 구축하고 배포하는 방법을 다룬 실전 지침서다. 아마존 EC2, 아마존 EBS, 아마존 다이나모DB, AWS 람다, AWS IAM을 비롯한 다양한 AWS 서비스를 사용하여 데이터 수집 및 처리, 머신러닝, 보안을 다룬다. 또한 AWS에서 데이터 과학 프로젝트의 비용을 절감하고 성능을 향상시키는 팁도 소개한다. 이 책을 따라 모든 학습을 마치고 나면 머신러닝 모델의 성능을 향상하기 위한 기술과 방법을 이해하고, AWS를 효과적으로 활용하여 머신러닝 모델을 구축하고 배포할 수 있게 될 것이다.
Statistical Physics
Suitable for graduate students in chemical physics, statistical physics, and physical chemistry, this text develops an innovative, probabilistic approach to statistical mechanics. The treatment employs Gauss's principle and incorporates Bose-Einstein and Fermi-Dirac statistics to provide a powerful tool for the statistical analysis of physical phenomena. The treatment begins with an introductory chapter on entropy and probability that covers Boltzmann's principle and thermodynamic probability, among other topics. Succeeding chapters offer a case history of black radiation, examine quantum and classical statistics, and discuss methods of processing information and the origins of the canonical distribution. The text concludes with explorations of statistical equivalence, radiative and material phase transitions, and the kinetic foundations of Gauss's error law. Bibliographic notes complete each chapter.
Nebraska History
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Enterprise Cybersecurity in Digital Business
Cyber risk is the highest perceived business risk according to risk managers and corporate insurance experts. Cybersecurity typically is viewed as the boogeyman: it strikes fear into the hearts of non-technical employees. Enterprise Cybersecurity in Digital Business: Building a Cyber Resilient Organization provides a clear guide for companies to understand cyber from a business perspective rather than a technical perspective, and to build resilience for their business. Written by a world-renowned expert in the field, the book is based on three years of research with the Fortune 1000 and cyber insurance industry carriers, reinsurers, and brokers. It acts as a roadmap to understand cybersecuri...
The Right One
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Machine Learning Engineering with MLflow
Get up and running, and productive in no time with MLflow using the most effective machine learning engineering approach Key FeaturesExplore machine learning workflows for stating ML problems in a concise and clear manner using MLflowUse MLflow to iteratively develop a ML model and manage it Discover and work with the features available in MLflow to seamlessly take a model from the development phase to a production environmentBook Description MLflow is a platform for the machine learning life cycle that enables structured development and iteration of machine learning models and a seamless transition into scalable production environments. This book will take you through the different features...
