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Damn This War!: Between the Blitz and the Desert, a Story of War-Crossed Love by Julie Hankey
English | February 13th, 2024 | ISBN: 1837730369 | 304 pages | True EPUB | 0.63 MB
The love story of Zippa and Tony is nothing without the context of the Second World War.

The war introduced them - they met as blackout wardens in London. It gave them darkened streets to wander in, hand in hand, then, by sending Tony away to officer training camps, it sharpened their hunger for each other, casting a glow over his comings and goings. It turned them into schemers and wanglers against fate and army regulations. It pressed them into marriage, and when the war decided to deploy him to North Africa, it whispered the urgent question of a baby. To which Tony, thinking of the war, replied maybe not; and Zippa, thinking of the war, said yes.
In spite of themselves, the war experience was changing them both, and yet both were hanging on, looking back, suspended in memory and time, and living from letter to letter.
Decades later, their daughter Julie discovered their letters, and piecing them together began to create a portrait of her parents and their relationship that was completely unfamiliar to her. Vivid, honest and completely absorbing, Damn This War! is a true insight into a wartime love story.

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Dancing with the Modernist City: Metropolitan Dance Texts around 1900 by Wesley Lim
English | July 22, 2024 | ISBN: 0472133306 | 324 pages | EPUB | 1.33 Mb
As the 20th century dawned, authors, artists, and filmmakers flocked to cities like Paris and Berlin for a chance to experience a bustling urban life and engage with other artists and intellectuals. Among them were German-speaking authors and filmmakers such as Harry Graf Kessler, Rainer Maria Rilke, August Endell, Alfred Döblin, Else Lasker-Schüler, Segundo de Chomón, and the brothers Max and Emil Skladanowsky. In their writing and artistic work from that period, they depicted the perpetual influx of stimuli caused by urban life-including hordes of pedestrians, bustling traffic, and a barrage of advertisements-as well as how these encounters repeatedly paralleled their experiences of watching early twentieth-century dance performances by Loïe Fuller, Ruth St. Denis, and Vaslav Nijinsky. The convergence these writers and filmmakers saw between the unexpected encounters during their urban strolls and experimental dance performances led to writings that interwove the two motifs.

Drawing on cultural, literary, dance, performance, and queer studies, Dancing with the Modernist City analyzes an array of material from 1896 to 1914-essays, novels, short stories, poetry, newspaper articles, photographs, posters, drawings, and early film. It argues that these writers and artists created a genre called the metropolitan dance text, which depicts dancing figures not on a traditional stage, but with the streets, advertising pillars, theaters, cafes, squares, and even hospitals of an urban setting. Breaking away from the historically male, heteronormative view, this posthumanist mode of writing highlights the visual and episodic unexpectedness of urban encounters. These literary depictions question traditional conceptualizations of space and performance by making the protagonist and the reader feel like they embody the dancer and the movement. In doing so, they upset the conventional depictions of performance and urban spaces in ways paralleling modern dance.

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David Cressy, "Dangerous Talk: Scandalous, Seditious, and Treasonable Speech in Pre-Modern England"
English | 2010 | pages: 391 | ISBN: 0199564809, 0199606099 | PDF | 2,3 mb
Dangerous Talk examines the "lewd, ungracious, detestable, opprobrious, and rebellious-sounding" speech of ordinary men and women who spoke scornfully of kings and queens. Eavesdropping on lost conversations, it reveals the expressions that got people into trouble, and follows the fate of some of the offenders. Introducing stories and characters previously unknown to history, David Cressy explores the contested zones where private words had public consequence. Though "words were but wind," as the proverb had it, malicious tongues caused social damage, seditious words challenged political authority, and treasonous speech imperiled the crown.

Royal regimes from the house of Plantagenet to the house of Hanover coped variously with "crimes of the tongue" and found ways to monitor talk they deemed dangerous. Their response involved policing and surveillance, judicial intervention, political propaganda, and the crafting of new law. In early Tudor times to speak ill of the monarch could risk execution. By the end of the Stuart era similar words could be dismissed with a shrug. This book traces the development of free speech across five centuries of popular political culture, and shows how scandalous, seditious and treasonable talk finally gained protection as "the birthright of an Englishman." The lively and accessible work of a prize-winning social historian, it offers fresh insight into pre-modern society, the politics of language, and the social impact of the law.

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Das Geburtsbuch: Vorbereiten - Erleben - Verarbeiten by Nora Imlau
German | May 9, 2016 | ISBN: 3407864078 | EPUB | 2.49 Mb
Vom Kaiserschnitt bis zur Hausgeburt breitet Nora Imlau das gesamte Spektrum des Gebärens aus und geht besonders auf die Emotionen der Mutter ein - vor, bei und nach der Geburt. Einfühlsam und mit großer Fachkenntnis hilft dieses Buch, das einzigartige Erlebnis vorzubereiten und nachklingen zu lassen.

Schwangere können heute vieles selbst bestimmen. Aber nicht alles. Bei jeder Geburt werden Sehnsüchte erfüllt und Vorstellungen enttäuscht. Nora Imlau zeigt, wie der Balanceakt individuell gelingt, sich optimal vorzubereiten und gleichzeitig achtsam zu sein für alles, was körperlich und seelisch passiert. Denn jede Geburt bringt auch eine veränderte Frau zur Welt.

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Das rote Erbe der Front: Der Erste Weltkrieg in der DDR
Deutsch | 2022 | ISBN: 3110710730 | 555 Pages | EPUB | 8 MB
Der Erste Weltkrieg darf nicht nur als die "Urkatastrophe des 20. Jahrhunderts" gesehen werden, sondern auch als eine fundamentale Grunderfahrung für die zukünftige Führungselite der DDR. Der Krieg hat ihren Leib und ihre Weltanschauung geprägt. Wie relevant war diese Erfahrung für die politischen Kämpfe der Weimarer Republik und den Widerstand unter dem Nationalsozialismus?

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Data & AI Imperative: Designing Strategies for Exponential Growth by Lillian Pierson
English | January 2nd, 2025 | ISBN: 1394251955 | 352 pages | True EPUB | 6.09 MB
Unlock predictable bottom line growth through tailored data and AI strategies.

In The Data & AI Imperative: Designing Strategies for Exponential Growth, celebrated data-driven growth leader, Lillian Pierson, delivers a masterclass in developing custom strategies to harness the full potential of data and AI within your organization. This book offers a clear, actionable roadmap for leveraging your company's data and technology assets to drive significant, reliable growth.
With over two decades of experience, Pierson unveils her proprietary STAR framework through which you'll learn to survey, take stock of, and assess your company's current state. Finally, you'll be guided on how to recommend strategies that drive growth via the execution of optimally positioned data- and AI- intensive projects or products that directly improve your business bottom line.
From conception to execution, learn to:
* Identify high-impact opportunities for data or AI interventions within your business.
* Assess your organization's readiness and data literacy to ensure successful outcomes.
* Implement practical, effective tactics for overseeing your data-intensive projects, from strategic plans to profitable realities.
* Develop and deploy AI and data strategies that exceed your business goals.
While ideal for executives, managers, and other leaders of data- or AI-intensive companies, The Data & AI Imperative is also invaluable to data and technical professionals who aspire to elevate their impact by turning technical expertise into strategic leadership success.

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[booksz]

Data & AI Imperative: Designing Strategies for Exponential Growth
English | 2024 | ISBN: 1394251955 | 415 Pages | PDF | 4.3 MB
In The Data & AI Imperative: Designing Strategies for Exponential Growth, celebrated data-driven growth leader, Lillian Pierson, delivers a masterclass in developing custom strategies to harness the full potential of data and AI within your organization. This book offers a clear, actionable roadmap for leveraging your company's data and technology assets to drive significant, reliable growth.

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Data Analytics and Machine Learning for Integrated Corridor Management by Yashawi Karnati, Dhruv Mahajan, Tania Banerjee
English | October 25, 2024 | ISBN: 103257464X | 242 pages | MOBI | 8.47 Mb
In an era defined by rapid urbanization and ever-increasing mobility demands, effective transportation management is paramount. This book takes readers on a journey through the intricate web of contemporary transportation systems, offering unparalleled insights into the strategies, technologies, and methodologies shaping the movement of people and goods in urban landscapes.

From the fundamental principles of traffic signal dynamics to the cutting-edge applications of machine learning, each chapter of this comprehensive guide unveils essential aspects of modern transportation management systems. Chapter by chapter, readers are immersed in the complexities of traffic signal coordination, corridor management, data-driven decision-making, and the integration of advanced technologies. Closing with chapters on modeling measures of effectiveness and computational signal timing optimization, the guide equips readers with the knowledge and tools needed to navigate the complexities of modern transportation management systems.
With insights into traffic data visualization and operational performance measures, this book empowers traffic engineers and administrators to design 21st-century signal policies that optimize mobility, enhance safety, and shape the future of urban transportation.

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Data Analytics and Machine Learning: Navigating the Big Data Landscape (Studies in Big Data, 145) by Pushpa Singh, Asha Rani Mishra, Payal Garg
ISBN: 9819704472 | MOBI | 23 Mb
This book presents an in-depth analysis of successful data-driven initiatives, highlighting how organizations have leveraged data to drive decision-making processes, optimize operations, and achieve remarkable outcomes. Through case studies, readers gain valuable insights and learn practical strategies for implementing data analytics, big data, and machine learning solutions in their own organizations. The book discusses the transformative power of data analytics and big data in various industries and sectors and how machine learning applications have revolutionized exploration by enabling advanced data analysis techniques for mapping, geospatial analysis, and environmental monitoring, enhancing our understanding of the world and its dynamic processes. This book explores how big data explosion, the power of analytics and machine learning revolution can bring new prospects and opportunities in the dynamic and data-rich landscape. It highlights the future research directions in data analytics, big data, and machine learning that explores the emerging trends, challenges, and opportunities in these fields by covering interdisciplinary approaches such as handling and analyzing real-time and streaming data.

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Data Cleaning with Power BI: The definitive guide to transforming dirty data into actionable insights by Gus Frazer
English | February 29th, 2024 | ISBN: 1805126407 | 340 pages | True PDF | 8.57 MB
Unlock the full potential of your data by mastering the art of cleaning, preparing, and transforming data with Power BI for smarter insights and data visualizations

Key Features:
* Implement best practices for connecting, preparing, cleaning, and analyzing multiple sources of data using Power BI
* Conduct exploratory data analysis (EDA) using DAX, PowerQuery, and the M language
* Apply your newfound knowledge to tackle common data challenges for visualizations in Power BI
Book Description:
Microsoft Power BI offers a range of powerful data cleaning and preparation options through tools such as DAX, Power Query, and the M language. However, despite its user-friendly interface, mastering it can be challenging. Whether you're a seasoned analyst or a novice exploring the potential of Power BI, this comprehensive guide equips you with techniques to transform raw data into a reliable foundation for insightful analysis and visualization.
This book serves as a comprehensive guide to data cleaning, starting with data quality, common data challenges, and best practices for handling data. You'll learn how to import and clean data with Query Editor and transform data using the M query language. As you advance, you'll explore Power BI's data modeling capabilities for efficient cleaning and establishing relationships. Later chapters cover best practices for using Power Automate for data cleaning and task automation. Finally, you'll discover how OpenAI and ChatGPT can make data cleaning in Power BI easier.
By the end of the book, you will have a comprehensive understanding of data cleaning concepts, techniques, and how to use Power BI and its tools for effective data preparation.
Who is this book for?
If you're a data analyst, business intelligence professional, business analyst, data scientist, or anyone who works with data on a regular basis, this book is for you. It's a useful resource for anyone who wants to gain a deeper understanding of data quality issues and best practices for data cleaning in Power BI. If you have a basic knowledge of BI tools and concepts, this book will help you advance your skills in Power BI.
What you will learn
* Connect to data sources using both import and DirectQuery options
* Use the Query Editor to apply data transformations
* Transform your data using the M query language
* Design clean and optimized data models by creating relationships and DAX calculations
* Perform exploratory data analysis using Power BI
* Address the most common data challenges with best practices
* Explore the benefits of using OpenAI, ChatGPT, and Microsoft Copilot for simplifying data cleaning

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Data Engineering with AWS: Building Next-Gen Data Architectures on AWS by May Sherry
English | September 3, 2024 | ISBN: N/A | ASIN: B0DG3X1BRJ | 78 pages | EPUB | 1.27 Mb
"Data Engineering with AWS: Building Next-Gen Data Architectures on AWS" is your comprehensive guide to mastering data engineering in the cloud. This book delves into the full spectrum of data engineering on the AWS platform, from foundational concepts to advanced techniques, enabling you to build, optimize, and scale data pipelines with confidence.

Designed for data engineers, cloud architects, and IT professionals, this book covers the latest AWS tools and services that power modern data solutions. You'll explore key topics such as data ingestion, transformation, storage, and analysis, all while leveraging AWS services like Amazon S3, Redshift, Glue, and Kinesis. The book provides practical, hands-on examples to demonstrate how to create robust, secure, and scalable data architectures that can handle the demands of big data and real-time analytics.
"Data Engineering with AWS" equips you with the knowledge and skills to harness the power of AWS for your data engineering needs. Learn how to implement best practices, optimize performance, and ensure data security while keeping costs under control. With this book, you'll be prepared to build the next generation of data-driven applications on AWS.

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Data Engineering with AWS: Building Scalable Data Pipelines in the Cloud by May Sherry
English | September 3, 2024 | ISBN: N/A | ASIN: B0DG3QNJ6P | 81 pages | EPUB | 1.32 Mb
"Data Engineering with AWS" goes beyond just theory, offering hands-on tutorials, best practices, and insights into emerging trends. You'll explore the latest advancements in AI, machine learning, and serverless computing, and how they are reshaping the future of data engineering in the cloud. Whether you're working with structured or unstructured data, this book equips you with the knowledge to harness AWS's full potential and drive innovation in your organization.

With its clear explanations, detailed examples, and step-by-step guidance, this book is an essential resource for anyone looking to build and manage scalable data pipelines on AWS. Unlock the power of cloud-based data engineering and take your skills to the next level with "Data Engineering with AWS: Building Scalable Data Pipelines in the Cloud."

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Data Science (Chapman & Hall/CRC Data Science Series) by Tiffany Timbers, Trevor Campbell, Melissa Lee
English | August 22, 2024 | ISBN: 103257223X | 452 pages | MOBI | 23 Mb
Data Science: A First Introduction with Python focuses on using the Python programming language in Jupyter notebooks to perform data manipulation and cleaning, create effective visualizations, and extract insights from data using classification, regression, clustering, and inference. It emphasizes workflows that are clear, reproducible, and shareable, and includes coverage of the basics of version control. Based on educational research and active learning principles, the book uses a modern approach to Python and includes accompanying autograded Jupyter worksheets for interactive, self-directed learning. The text will leave readers well-prepared for data science projects. It is designed for learners from all disciplines with minimal prior knowledge of mathematics and programming. The authors have honed the material through years of experience teaching thousands of undergraduates at the University of British Columbia.

Key Features:Includes autograded worksheets for interactive, self-directed learning.Introduces readers to modern data analysis and workflow tools such as Jupyter notebooks and GitHub, and covers cutting-edge data analysis and manipulation Python libraries such as pandas, scikit-learn, and altair.Is designed for a broad audience of learners from all backgrounds and disciplines.

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Data Science for Decision Makers: Enhance your leadership skills with data science and AI expertise by John Howells
English | July 26th, 2024 | ISBN: 1837637296 | 270 pages | True PDF | 5.11 MB
Bridge the gap between business and data science by learning how to interpret machine learning and AI models, manage data teams, and achieve impactful results

Key Features:
* Master the concepts of statistics and ML to interpret models and guide decisions
* Identify valuable AI use cases and manage data science projects from start to finish
* Empower top data science teams to solve complex problems and build AI products
Book Description:
As data science and artificial intelligence (AI) become prevalent across industries, executives without formal education in statistics and machine learning, as well as data scientists moving into leadership roles, must learn how to make informed decisions about complex models and manage data teams.
This book will elevate your leadership skills by guiding you through the core concepts of data science and AI. This comprehensive guide is designed to bridge the gap between business needs and technical solutions, empowering you to make informed decisions and drive measurable value within your organization. Through practical examples and clear explanations, you'll learn how to collect and analyze structured and unstructured data, build a strong foundation in statistics and machine learning, and evaluate models confidently. By recognizing common pitfalls and valuable use cases, you'll plan data science projects effectively, from the ground up to completion. Beyond technical aspects, this book provides tools to recruit top talent, manage high-performing teams, and stay up to date with industry advancements.
By the end of this book, you'll be able to characterize the data within your organization and frame business problems as data science problems.
Who is this book for?
This book is designed for executives who want to understand and apply data science methods to enhance decision-making. It is also for individuals who work with or manage data scientists and machine learning engineers, such as chief data officers (CDOs), data science managers, and technical project managers.
What you will learn
* Discover how to interpret common statistical quantities and make data-driven decisions
* Explore ML concepts as well as techniques in supervised, unsupervised, and reinforcement learning
* Find out how to evaluate statistical and machine learning models
* Understand the data science lifecycle, from development to monitoring of models in production
* Know when to use ML, statistical modeling, or traditional BI methods
* Manage data teams and data science projects effectively

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Data Science Training - Supervised Learning: Ein praktischer Einstieg ins überwachte maschinelle Lernen
Deutsch | 2024 | ISBN: 3662679590 | 595 Pages | PDF (True) | 12 MB
Dieses Lehrbuch erklärt auf narrative und direkte Weise die wichtigen Zusammenhänge zwischen Data Science, Künstlicher Intelligenz und anderen Disziplinen und Domänen wie Datenschutz und Ethik, mit Fokus auf überwachtes Lernen (Supervised Learning).Wir begleiten Anna und Karl während ihrer Traineephase in einer internationalen Versicherung. Schritt für Schritt reifen sie zu Data Scientists, indem sie sich intensiv mit der Titanic-Katastrophe auseinandersetzen. Anna kann Python programmieren, während Karl ein grafisches Werkzeug (KNIME Analytics Platform) benutzt. Bei ihren Untersuchungen stoßen sie auf interessante Fakten und Mythen. Mit Unterstützung von Max und Sophia verarbeiten sie historische Daten, um Vorhersagen zu erstellen (Predictive Analytics). Dabei benutzen sie Methoden und Algorithmen des maschinellen Lernens.Begleitende Zusatzmaterialien (KNIME Workflows, Jupyter Notebooks, Erklärvideos) stehen den Lernenden online zur Verfügung. Und wenn in diesemBuch Anna und Karl sich auf Themen des überwachten Lernens konzentrieren, werden wir künftig mit ihnen noch weitere Gebiete der Data Science entdecken.

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