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Das XXL Ninja Heißluftfritteuse Rezeptbuch
Deutsch | 2025 | ASIN: B0DTPCG88W | 98 Pages | PDF | 19 MB
Dieses farbig gestaltete Kochbuch wurde mit viel Liebe zum Detail entworfen, um Ihnen ein großartiges Kocherlebnis zu bieten. Mit seinem XXL-Design, großen Buchstaben und einer übersichtlichen Struktur ist es ideal für jede Küche und besonders praktisch für ältere Benutzer.
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Das XXL Russell Hobbs Heißluftfritteuse Familien-Kochbuch
Deutsch | 2025 | ASIN: B0DV5FL1SX | 265 Pages | EPUB | 30 MB
Stellen Sie sich vor, wie Sie Tag für Tag zwischen aufwendigen, langweiligen Rezepten und schnellen, aber ungesunden Fertiggerichten gefangen sind. Sie wollen endlich mehr Geschmack, mehr Gesundheit und vor allem mehr Zeit für das, was wirklich zählt: Ihre Familie und Ihr Wohlbefinden.
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Data & AI Imperative: Designing Strategies for Exponential Growth by Lillian Pierson
English | January 2nd, 2025 | ISBN: 1394251955 | 351 pages | True PDF | 6.85 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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Rapidgator
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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 | AZW3 | 8.52 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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Rapidgator
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TakeFile
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Data Analytics for Finance Using Python (Advances in Digital Technologies for Smart Applications) by Nitin Jaglal Untwal, Utku Kose
English | December 30, 2024 | ISBN: 103261823X | 138 pages | MOBI | 7.02 Mb
Unlock the power of data analytics in finance with this comprehensive guide. Data Analytics for Finance Using Python is your key to unlocking the secrets of the financial markets.
In this book, you'll discover how to harness the latest data analytics techniques, including machine learning and inferential statistics, to make informed investment decisions and drive business success. With a focus on practical application, this book takes you on a journey from the basics of data preprocessing and visualization to advanced modeling techniques for stock price prediction.
Through real-world case studies and examples, you'll learn how to:Uncover hidden patterns and trends in financial dataBuild predictive models that drive investment decisionsOptimize portfolio performance using data-driven insightsStay ahead of the competition with cutting-edge data analytics techniquesWhether you're a finance professional seeking to enhance your data analytics skills or a researcher looking to advance the field of finance through data-driven insights, this book is an essential resource. Dive into the world of data analytics in finance and discover the power to make informed decisions, drive business success, and stay ahead of the curve.
This book will be helpful for students, researchers, and users of machine learning and financial tools in the disciplines of commerce, management, and economics.
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Data Analytics for Intelligent Systems: Techniques and Solutions (Iop Ebooks) by Sachin Taran, Chhavi Dhiman, Manjeet Kumar
English | May 14, 2024 | ISBN: 0750354151 | 271 pages | AZW3 | 14 Mb
This book focuses on the theory, development, novel techniques, and smart solutions in data analytics for intelligent systems that capture behaviours in complex environments. It focuses on the various advanced techniques in data analytics that can be used in different domains to solve real-time problems.
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Data Analytics: Models and Algorithms for Intelligent Data Analysis - A Comprehensive Introduction
English | 2025 | ISBN: 3658459506 | 197 Pages | PDF (True) | 6 MB
This book is a comprehensive introduction to the methods and algorithms of modern data analytics. It provides a sound mathematical basis, discusses advantages and drawbacks of different approaches, and enables the reader to design and implement data analytics solutions for real-world applications. The new edition integrates themes such as Word Embeddings, Transformer Models, and generative AI among the contents and offers new exercises in addition. This book has been used for more than ten years in the Data Mining course at the Technical University of Munich. Much of the content is based on the results of industrial research and development projects at Siemens.
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Rapidgator
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Data Architectures
by Prabhat Kumar
English | December 28, 2024 | ISBN: 0008653496 | 161 Pages | True epub | 0,22 MB
In the rapidly evolving landscape of modern technology, data has emerged as one of the most valuable assets for businesses, governments, and individuals alike. Every decision made, every process optimized, and every innovation generated is underpinned by data. From large enterprises to startups, from healthcare to finance, data drives insights, powers automation, and fuels machine learning and artificial intelligence. But despite its vast potential, data can be overwhelming-unstructured, inconsistent, and distributed across diverse systems and platforms.
Data architecture, the framework for organizing, managing, and integrating this data, has never been more critical. It is the backbone that allows organizations to turn raw data into actionable insights. The design of your data architecture-whether centralized, decentralized, or hybrid-determines how efficiently and securely data flows, is stored, and is accessed within your ecosystem. The choice of architecture has significant implications for performance, scalability, data governance, and ultimately, the success of a data-driven strategy.
This book aims to provide a comprehensive guide to the field of data architecture, with a focus on three major architectural paradigms: centralized, decentralized, and hybrid. These architectures represent different approaches to organizing data in a way that best supports an organization's needs, goals, and infrastructure. Understanding each of these models is essential for anyone working in data management, data engineering, or any role where data is leveraged for decision-making
eBook Details:
Prabhat Kumar
161 Pages
3 - 4 Hours to read
50k Total words
Release Date: December 28, 2024
ISBN-13: 1230008653499
ISBN-10: 0008653496
Language: English
Format: epub
File Size: 0,22 MB
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Data Engineering with Google Cloud Platform: A guide to leveling up as a data engineer by building a scalable data platform with Google Cloud by Adi Wijaya
English | April 30, 2024 | ISBN: 1835080111 | 476 pages | EPUB | 21 Mb
Become a successful data engineer by building and deploying your own data pipelines on Google Cloud, including making key architectural decisions
Key FeaturesGet up to speed with data governance on Google CloudLearn how to use various Google Cloud products like Dataform, DLP, Dataplex, Dataproc Serverless, and DatastreamBoost your confidence by getting Google Cloud data engineering certification guidance from real exam experiencesPurchase of the print or Kindle book includes a free PDF eBookBook Description
The second edition of Data Engineering with Google Cloud builds upon the success of the first edition by offering enhanced clarity and depth to data professionals navigating the intricate landscape of data engineering.
Beyond its foundational lessons, this new edition delves into the essential realm of data governance within Google Cloud, providing you with invaluable insights into managing and optimizing data resources effectively. Written by a Data Strategic Cloud Engineer at Google, this book helps you stay ahead of the curve by guiding you through the latest technological advancements in the Google Cloud ecosystem. You'll cover essential aspects, from exploring Cloud Composer 2 to the evolution of Airflow 2.5. Additionally, you'll explore how to work with cutting-edge tools like Dataform, DLP, Dataplex, Dataproc Serverless, and Datastream to perform data governance on datasets.
By the end of this book, you'll be equipped to navigate the ever-evolving world of data engineering on Google Cloud, from foundational principles to cutting-edge practices.
What you will learnLoad data into BigQuery and materialize its outputFocus on data pipeline orchestration using Cloud ComposerFormulate Airflow jobs to orchestrate and automate a data warehouseEstablish a Hadoop data lake, generate ephemeral clusters, and execute jobs on the Dataproc clusterHarness Pub/Sub for messaging and ingestion for event-driven systemsApply Dataflow to conduct ETL on streaming dataImplement data governance services on Google CloudWho this book is for
Data analysts, IT practitioners, software engineers, or any data enthusiasts looking to have a successful data engineering career will find this book invaluable. Additionally, experienced data professionals who want to start using Google Cloud to build data platforms will get clear insights on how to navigate the path. Whether you're a beginner who wants to explore the fundamentals or a seasoned professional seeking to learn the latest data engineering concepts, this book is for you.
Table of ContentsFundamentals of Data engineering with GCPBig Data Capabilities on GCPBuilding a data warehouse in BigQueryBuild Orchestration for Batch Data Loading Using Cloud ComposerBuilding a Data Lake using DataprocProcess Streaming Data with Datastream, Pub/Sub and DataflowVisualizing Data for Making Data-Driven Decisions with Looker StudioBuild machine learning solutions on GCPUser and Project Management on GCPData Governance in GCPCost Strategy in GCPCI/CD on Google Cloud Platform for Data EngineersBoost your confidence as a Data Engineer
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Rapidgator
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Data Engineering with Google Cloud Platform: A guide to leveling up as a data engineer by building a scalable data platform with Google Cloud by Adi Wijaya
English | April 30, 2024 | ISBN: 1835080111 | 476 pages | PDF | 45 Mb
Become a successful data engineer by building and deploying your own data pipelines on Google Cloud, including making key architectural decisions
Key FeaturesGet up to speed with data governance on Google CloudLearn how to use various Google Cloud products like Dataform, DLP, Dataplex, Dataproc Serverless, and DatastreamBoost your confidence by getting Google Cloud data engineering certification guidance from real exam experiencesPurchase of the print or Kindle book includes a free PDF eBookBook Description
The second edition of Data Engineering with Google Cloud builds upon the success of the first edition by offering enhanced clarity and depth to data professionals navigating the intricate landscape of data engineering.
Beyond its foundational lessons, this new edition delves into the essential realm of data governance within Google Cloud, providing you with invaluable insights into managing and optimizing data resources effectively. Written by a Data Strategic Cloud Engineer at Google, this book helps you stay ahead of the curve by guiding you through the latest technological advancements in the Google Cloud ecosystem. You'll cover essential aspects, from exploring Cloud Composer 2 to the evolution of Airflow 2.5. Additionally, you'll explore how to work with cutting-edge tools like Dataform, DLP, Dataplex, Dataproc Serverless, and Datastream to perform data governance on datasets.
By the end of this book, you'll be equipped to navigate the ever-evolving world of data engineering on Google Cloud, from foundational principles to cutting-edge practices.
What you will learnLoad data into BigQuery and materialize its outputFocus on data pipeline orchestration using Cloud ComposerFormulate Airflow jobs to orchestrate and automate a data warehouseEstablish a Hadoop data lake, generate ephemeral clusters, and execute jobs on the Dataproc clusterHarness Pub/Sub for messaging and ingestion for event-driven systemsApply Dataflow to conduct ETL on streaming dataImplement data governance services on Google CloudWho this book is for
Data analysts, IT practitioners, software engineers, or any data enthusiasts looking to have a successful data engineering career will find this book invaluable. Additionally, experienced data professionals who want to start using Google Cloud to build data platforms will get clear insights on how to navigate the path. Whether you're a beginner who wants to explore the fundamentals or a seasoned professional seeking to learn the latest data engineering concepts, this book is for you.
Table of ContentsFundamentals of Data engineering with GCPBig Data Capabilities on GCPBuilding a data warehouse in BigQueryBuild Orchestration for Batch Data Loading Using Cloud ComposerBuilding a Data Lake using DataprocProcess Streaming Data with Datastream, Pub/Sub and DataflowVisualizing Data for Making Data-Driven Decisions with Looker StudioBuild machine learning solutions on GCPUser and Project Management on GCPData Governance in GCPCost Strategy in GCPCI/CD on Google Cloud Platform for Data EngineersBoost your confidence as a Data Engineer
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Joseph Lee, "Data Governance in AI, FinTech and LegalTech: Law and Regulation in the Financial Sector"
English | ISBN: 1800379943 | 2022 | 320 pages | PDF | 1273 KB
Advocating for more standardised data governance practices and promoting the digital economy, Data Governance in AI, FinTech and LegalTech investigates the rationale, legal base and tools of data governance in the financial sector. This timely book makes a significant contribution to the debate around how rapidly-evolving digital finance practices should be regulated.
Contributions from leading researchers examine a range of financial services, offering a comprehensive assessment of the available tools for constructing multi-layered matrix systems for data governance in the financial services sector. Chapters explore data governance in the cryptocurrency market, crypto-asset providers, legal services for mergers and acquisitions, consumer insurance, consumer finance, digital platform services, securities exchanges and the green bond market. The book serves to define the legal contours of data governance, taking account of the influence of shifting business models, the views of multiple stakeholders and emerging issues surrounding data protection, privacy and cybersecurity.
Read more
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Data Governance with Unity Catalog on Databricks
English | 2025 | ISBN: 9781098179625 | 86 Pages | EPUB | 9 MB
Organizations collecting and using personal data must now heed a growing body of regulations, and the penalties for noncompliance are stiff. The ubiquity of the cloud and the advent of generative AI have only made it more crucial to govern data appropriately. Thousands of companies have turned to Databricks Unity Catalog to simplify data governance and manage their data and AI assets more effectively. This practical guide helps you do the same.
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Data Independence: Reclaiming Privacy in an Era of Evolving Tech by Wes Chaar
English | September 24, 2024 | ISBN: 1642259756 | 176 pages | PDF | 3.89 Mb
In the digital age, our personal data has become a valuable commodity, sought after by corporations, organizations, and governments alike. Data Independence: Reclaiming Privacy in an Era of Evolving Tech is a groundbreaking book by data scientist Wes Chaar that exposes the hidden world of the data economy and offers a revolutionary solution to reclaim our data rights.
With over twenty years of experience in the data space, Chaar reveals some of the hidden techniques used to collect, analyze, and monetize our personal information without our complete knowledge or understanding. From our daily activities, online behavior and purchases, and social media interactions to location tracking and biometric data, every aspect of our lives is being monitored and compiled into a digital dossier, which provides significant insights into an individual and monetization opportunities for corporations.
Data Independence is more than just a revelation―it's a revolution to reclaim your rights. Chaar introduces the Personal Data Vault Key, a tool concept that puts individuals in control of their data. By leveraging the principles of data consent, control, and currency, everyone is in charge of their data. This creates transparency, accountability, protection, equality, and respect between you and the entities you allow to use your data assets on your terms. The Personal Data Vault Key empowers users to decide who accesses their data, how it's used, and even how to monetize it.
Through compelling case studies, expert insights, and practical guidance, Data Independence demystifies the complex world of data privacy and provides readers with the knowledge and tools they need to protect their data power. Chaar's engaging and accessible writing style makes even the most technical concepts easy to understand, while his passionate advocacy for privacy rights is both inspiring and empowering.
Whether you're concerned about your offline and online privacy, curious about the inner workings of the data economy, or seeking to leverage your personal data for your own benefit, Data Independence is an essential read. It's a call to action for a data revolution―one that puts the power back in the hands of the people.
Join Wes Chaar on this transformative journey and discover how to unlock the power of personal data control. Your data future starts here.
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Data Migration for SAP: SAP S/4HANA and Cloud Solutions (SAP PRESS) by Frank Finkbohner, Martina Höft, Michael Roth
English | May 29, 2024 | ISBN: 1493225227 | 600 pages | MOBI | 33 Mb
Whether you're moving to the cloud, migrating to SAP S/4HANA, or replacing a legacy system, get the data migration guidance you need in this comprehensive guide. Evaluate your landscape options and plan your strategy; then walk through the migration processes for SAP S/4HANA, SAP SuccessFactors, SAP Ariba, and SAP Business ByDesign. Master built-in tools and templates, IDoc and ALE distribution models, batch input, Cloud Integration from SAP Integration Suite, and more!Plan and execute SAP data migration without programmingLearn to migrate data to SAP S/4HANA, SAP SuccessFactors, SAP Ariba, and SAP Business ByDesignExplore migration tools including Cloud Integration, SAP Legacy System Migration Workbench, batch input, IDocs, and ALE
Data Migration Basics
Review the technical fundamentals of data migration in an easy-to-understand way. Compare migration strategies and scenarios-including greenfield, brownfield, and hybrid implementations-and learn how to plan your migration project efficiently from start to finish.
SAP Solution Migration
Follow step-by-step instructions to migrate data to SAP systems. See how the migration cockpit and the migration object modeler ease the transition to SAP S/4HANA, and get expert guidance for migrating to cloud-based solutions like SAP SuccessFactors, SAP Ariba, and SAP Business ByDesign.
Migration Approaches
Learn to use classic migration methods, including IDoc and ALE distribution models, batch input, and database migration. Convert data types and data constellations without the need for programming. Use SAP Legacy System Migration Workbench and Cloud Integration to seamlessly transition data between different systems.PlanningSAP S/4HANASAP S/4HANA CloudSAP SuccesFactorsSAP AribaSAP Business ByDesignSAP Legacy System Migration WorkbenchSAP S/4HANA migration cockpitCloud IntegrationSAP S/4HANA migration object modelerBatch inputIDoc and ALE distribution models
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Data Science and Applications for Modern Power Systems (Power Electronics and Power Systems) by Le Xie, Yang Weng, Ram Rajagopal
English | June 21, 2023 | ISBN: 3031290992 | 451 pages | MOBI | 41 Mb
This book offers a comprehensive collection of research articles that utilize data―in particular large data sets―in modern power systems operation and planning. As the power industry moves towards actively utilizing distributed resources with advanced technologies and incentives, it is becoming increasingly important to benefit from the available heterogeneous data sets for improved decision-making. The authors present a first-of-its-kind comprehensive review of big data opportunities and challenges in the smart grid industry. This book provides succinct and useful theory, practical algorithms, and case studies to improve power grid operations and planning utilizing big data, making it a useful graduate-level reference for students, faculty, and practitioners on the future grid.
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Data Science and Network Engineering: Proceedings ICDSNE 2024
English | 2025 | ISBN: 9819783356 | 654 Pages | PDF EPUB (True) | 70 MB
This book includes research papers presented at the International Conference on Data Science and Network Engineering (ICDSNE 2024) organized by the Department of Computer Science and Engineering, National Institute of Technology Agartala, Tripura, India, during July 12-13, 2024. It includes research works from researchers, academicians, business executives, and industry professionals for solving real-life problems by using the advancements and applications of data science and network engineering. This book covers many advanced topics, such as artificial intelligence (AI), machine learning (ML), deep learning (DL), computer networks, blockchain, security and privacy, Internet of things (IoT), cloud computing, big data, supply chain management, and many more. Different sections of this book are highly beneficial for the researchers, who are working in the field of data science and network engineering.
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Data Science e Machine Learning - Seconda Edizione
by Michele di Nuzzo
Italian | January 6, 2025 | ISBN: 0008675945 | 522 Pages | True epub | 6,61 MB
In un'era in cui i dati sono considerati il nuovo petrolio, capire come estrarre valore da essi è diventato essenziale per qualsiasi professionista o azienda che voglia rimanere competitiva. "Data Science e Machine Learning" di Michele di Nuzzo è la guida definitiva per chi desidera immergersi nel mondo della scienza dei dati, apprendere le tecniche di machine learning più avanzate e scoprire come applicarle ai problemi reali.
Contenuto
Questo libro offre:
Una panoramica dettagliata della scienza dei dati, delle sue origini e della sua evoluzione.
I fondamenti matematici e gli strumenti statistici per l'analisi e la modellazione dei dati
Elementi di statistica decrittiva, inferenziale e teoria della probabilità
Fondamenti di Machine Learning: spiegazioni chiare e concise dei principali algoritmi di apprendimento automatico, dai più semplici ai più complessi.
Tecniche per la modellazione e la validazione dei modelli di machine learning.
Esempi ed esercizi pratici per mettere subito in pratica le competenze acquisite.
Una guida completa sugli strumenti più utilizzati nel campo, da Python, NumPy, Pandas, MatDescriptionlib, Scikit-learn e altre librerie essenziali.
Capitoli dedicati a tecniche avanzate come l'apprendimento non supervisionato, l'apprendimento semi-supervisionato e i metodi ensamble.
A chi è rivolto questo libro
Questo libro è rivolto a chiunque voglia imparare a manipolare ed analizzare i dati traendo da questi nuova conoscenza. Se sei un manager IT o un analista che vuole entrare nel mondo della Data Science e dei Big Data, se sei uno sviluppatore che vuole conoscere le nuove tendenze nel campo dell'apprendimento automatico o sei semplicemente curioso di conoscere questo mondo, allora questo libro è per te.
eBook Details:
Michele di Nuzzo
522 Pages
10 - 11 Hours to read
132k Total words
Release Date: January 6, 2025
ISBN-13: 1230008675941
ISBN-10: 0008675945
Language: Italian
Format: epub
File Size: 6,61 MB
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Data Science for Political Campaigns: Winning with Analytics. Python, Excel & R: Reactive Publishing by Hayden Van Der Post, Reactive Publishing
English | January 21, 2025 | ISBN: N/A | ASIN: B0DTN6H25X | 390 pages | EPUB | 1.29 Mb
Reactive Publishing
Revolutionize Political Campaigning with the Power of Data Science
In the modern political arena, analytics isn't optional-it's the game changer. Data Science for Political Campaigns: Winning with Analytics is your essential guide to leveraging data science techniques to craft smarter, more targeted, and more effective campaigns.
This book provides a practical roadmap for political strategists, campaign managers, and data professionals looking to harness the full potential of data-driven decision-making. From voter segmentation to real-time performance tracking, you'll learn how to apply cutting-edge analytics to every stage of the campaign process.
What You'll Discover:Voter Segmentation: Use clustering and classification to identify key voter groups and their preferences.Predictive Analytics: Forecast voter turnout, election outcomes, and donation trends using machine learning models.Targeted Outreach: Optimize campaign messages and advertising with personalized insights.Social Media Analytics: Monitor and influence public sentiment through advanced sentiment analysis.Geo-Spatial Insights: Leverage geospatial data to optimize grassroots efforts and identify high-priority regions.Real-Time Dashboards: Build and deploy live campaign performance trackers using Python, R, or Tableau.Whether you're running a local city council campaign or managing a national election, this book offers actionable tools and strategies to take your campaign to the next level. With real-world examples, code snippets, and easy-to-follow tutorials, Data Science for Political Campaigns empowers you to win with data.
Take the guesswork out of politics and start running campaigns that win.
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Data Science from Scratch: A Complete Beginner's Guide to Mastering Analytics,
Machine Learning, and Real-World Applications
English | 2025 | ASIN : B0DXBYJ24Z | 97 Pages | EPUB | 1.3 MB
Are you ready to dive into the world of data science but don't know where to start? Data Science from Scratch is your ultimate beginner-friendly guide to building a strong foundation in analytics, machine learning, and real-world applications-without needing a PhD in math or programming.
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Data Science in Engineering Vol. 10
English | 2025 | ISBN: 303168141X | 141 Pages | PDF (True) | 18 MB
Data Science in Engineering, Volume 10: Proceedings of the 42nd IMAC, A Conference and Exposition on Structural Dynamics, 2024, the tenth volume of ten from the Conference brings together contributions to this important area of research and engineering. The collection presents early findings and case studies on fundamental and applied aspects of Data Science in Engineering, including papers on:
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