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Malam-Bouraima C: Business Forecasting
unter Einsatz von Machine Learning und

Business Forecasting unter Einsatz von Machine Learning und Business Intelligence

Eine Analyse auf Basis eines öffentlich zugänglichen Datensatzes

Platform Supply Chains in the AI Era

This open access book provides a systematic and in-depth analysis of the critical risks inherent in modern platform-based supply chains. Employing rigorous analytical methods, including game theory and advanced, computationally efficient simulation techniques, it delves into three core areas: operational risks, information and data risks, and quality and compliance risks. The book moves beyond traditional supply chain paradigms to address challenges unique to the platform economy. This includes the strategic threat of platforms using seller data to launch competing products, the complex trade-offs in managing third-party product quality, the impact of reactive capacity on quality decisions, and the challenge of optimizing inventory across networks of unprecedented scale.
 
 It is an essential resource for graduate students, academic researchers, and advanced practitioners in the fields of operations management, supply chain management, and information systems. The content is suitable for readers with a graduate-level understanding of these disciplines.

Risk Management

Platform Supply Chains 5

AN INSTANT NATIONAL BESTSELLER “Evenhanded and insightful.”&nbsp; —Publisher’s Weekly (starred review) “An accessible, often fascinating primer.... Essential, illuminating reading.” —Kirkus From the author of the New York Times bestseller The Digital Doctor comes an engaging, clear-eyed, and ultimately hopeful examination of healthcare’s efforts to embrace generative artificial intelligence. In A Giant Leap, physician and thought leader Robert Wachter navigates between hype and skepticism to make a compelling case for AI’s power to transform healthcare. He argues that, in a system buckling under the weight of bureaucratic pressures, soaring costs, and clinician burnout, AI doesn’t need to be perfect—it only needs to be better. Drawing on extensive research and more than 100 interviews with pioneers across medicine, technology, policy, and business, Wachter shows how AI is already entering hospitals and clinics to draft notes, field patient questions, recommend treatments, interpret images, and guide surgeries. He unflinchingly confronts risks like hallucinations, biases, and misinformation, while revealing how AI can now match, and sometimes surpass, physicians in areas ranging from diagnosis to empathy. But this isn’t simply a technology story. It’s about the human choices that will determine whether AI becomes healthcare’s salvation or another source of harm and frustration.&nbsp; Blending clinical insight, vivid storytelling, and journalistic precision, A Giant Leap offers an indispensable roadmap for healthcare leaders, clinicians, and patients. It&nbsp;is a vibrant and timely account of how AI is changing what it means to care—and be cared for—in this age of astonishing technology.

AN INSTANT NATIONAL BESTSELLER “Evenhanded and insightful.”&nbsp; —Publisher’s Weekly (starred review) “An accessible, often fascinating primer.... Essential, illuminating reading.” —Kirkus From the author of the New York Times bestseller The Digital Doctor comes an engaging, clear-eyed, and ultimately hopeful examination of healthcare’s efforts to embrace generative artificial intelligence. In A Giant Leap, physician and thought leader Robert Wachter navigates between hype and skepticism to make a compelling case for AI’s power to transform healthcare. He argues that, in a system buckling under the weight of bureaucratic pressures, soaring costs, and clinician burnout, AI doesn’t need to be perfect—it only needs to be better. Drawing on extensive research and more than 100 interviews with pioneers across medicine, technology, policy, and business, Wachter shows how AI is already entering hospitals and clinics to draft notes, field patient questions, recommend treatments, interpret images, and guide surgeries. He unflinchingly confronts risks like hallucinations, biases, and misinformation, while revealing how AI can now match, and sometimes surpass, physicians in areas ranging from diagnosis to empathy. But this isn’t simply a technology story. It’s about the human choices that will determine whether AI becomes healthcare’s salvation or another source of harm and frustration.&nbsp; Blending clinical insight, vivid storytelling, and journalistic precision, A Giant Leap offers an indispensable roadmap for healthcare leaders, clinicians, and patients. It&nbsp;is a vibrant and timely account of how AI is changing what it means to care—and be cared for—in this age of astonishing technology.

How AI Is Transforming Healthcare and What That Means for Our Future

A Giant Leap

Innovations in Intelligent Internet of Everything IoE

Biomedical Applications of AI and IoMT in Smart Healthcare

Asset Analytics

This book explores the transformative potential of Business Analytics in the modern business landscape, offering a practical guide to leveraging data for strategic decision-making. With companies generating vast amounts of data, there is a growing need for professionals who can interpret and analyze this information to derive actionable insights. This book equips readers with essential tools and techniques to become proficient in business analytics, emphasizing the application of data to solve real-world business problems and drive profitability. Encompassing various facets of a business, including supply chain analytics, HR analytics, influencer networks, Impact of machine learning and AR/VR, sensitivity analysis, data story telling etc. and even empowering customers with the help of data driven approach, this book tries to add value in managerial decision making. &nbsp;Focusing on the latest trends and advancements, this book demonstrates how analytics can provide a competitive edge by converting large datasets into meaningful insights. Through real-world examples and case studies, it shows how businesses can enhance market share and deliver greater returns to shareholders. Designed for business professionals, analysts, and decision-makers, this book is an essential resource for anyone looking to improve their company’s performance or advance their career with cutting-edge analytical skills.

This book explores the transformative potential of business analytics in the modern business landscape, offering a practical guide to leveraging data for strategic decision-making. With companies generating vast amounts of data, there is a growing need for professionals who can interpret and analyze this information to derive actionable insights. This book equips readers with essential tools and techniques to become proficient in business analytics, emphasizing the application of data to solve real-world business problems and drive profitability. Encompassing various facets of a business, including supply chain analytics, HR analytics, influencer networks, Impact of machine learning and AR/VR, sensitivity analysis, data story telling etc. and even empowering customers with the help of data driven approach, this book tries to add value in managerial decision making. &nbsp;Focusing on the latest trends and advancements, this book demonstrates how analytics can provide a competitive edge by converting large datasets into meaningful insights. Through real-world examples and case studies, it shows how businesses can enhance market share and deliver greater returns to shareholders. Designed for business professionals, analysts, and decision-makers, this book is an essential resource for anyone looking to improve their company’s performance or advance their career with cutting-edge analytical skills.

Sharpening beyond Data

Business Analytics and Managerial Decision Making

Security, Audit and Leadership Series

In an era where cyber threats evolve faster than traditional defenses can adapt, the need for a paradigm shift in cybersecurity auditing has never been more urgent. Transforming Cybersecurity Audit Practices with Agility and Artificial Intelligence (AI) presents a groundbreaking approach to modernizing audit methodologies.

Transforming Cybersecurity Audit Practices with Agility and Artificial Intelligence (AI)

Learning AutoML is your practical guide to applying automated machine learning in real-world environments. Whether you're a data scientist, ML engineer, or AI researcher, this book helps you move beyond experimentation to build and deploy high-performing models with less manual tuning and more automation. Using AutoGluon as a primary toolkit, you'll learn how to build, evaluate, and deploy AutoML models that reduce complexity and accelerate innovation. Author Kerem Tomak shares insights on how to integrate models into end-to-end deployment workflows using popular tools like Kubeflow, MLflow, and Airflow, while exploring cross-platform approaches with Vertex AI, SageMaker Autopilot, Azure AutoML, Auto-sklearn, and H2O.ai. Real-world case studies highlight applications across finance, healthcare, and retail, while chapters on ethics, governance, and agentic AI help future-proof your knowledge. <ul> <li>Build AutoML pipelines for tabular, text, image, and time series data</li> <li>Deploy models with fast, scalable workflows using MLOps best practices</li> <li>Compare and navigate today's leading AutoML platforms</li> <li>Interpret model results and make informed decisions with explainability tools</li> <li>Explore how AutoML leads into next-gen agentic AI systems</li> </ul>

Automating ML Pipelines with Autogluon, Leading Frameworks, and Real-World Integration

Learning Automl

A timely, practical guide to AI—its strengths, weaknesses, and real-world applications—for business professionals and policymakers. Artificial intelligence, or AI, can recognize a pattern from any set of data it is given, which is what makes it such an extraordinarily powerful tool. But because not all patterns are authentic or reliable, AI's pattern-finding superpower can lead to spurious patterns—and to disastrous results for business and government entities that rely on them. Hence the conundrum at the heart of AI: its greatest strength can also be its greatest weakness. Targeting the businessperson who needs to know how to use AI profitably and responsibly, Caleb Briggs and Rex Briggs offer in this book a foundational understanding of AI that is easy to grasp yet thorough enough to be used effectively.

A timely, practical guide to AI its strengths, weaknesses, and real-world applications for business professionals and policymakers.

Harnessing the Power of AI for Your Organization—Profitably and Safely

The AI Conundrum

A Financial Times Best Book of the Year A groundbreaking exploration of the shifting landscape of technological innovation and how it has transformed into a global phenomenon, challenging the traditional dominance of Silicon Valley. The US is the source of just about all the technologies that define modern life: personal computers, operating systems, smartphones, e-commerce, web browsers, email, search engines, social networks, electric cars, and the rest. And most of the tech companies that created and monetized these technologies are also in the US. In this book, Mehran Gul, the winner of the Financial Times/McKinsey Bracken Bower Prize, asks: is that changing? Less than a decade ago, the sentiment towards Chinese tech compa­nies was often dismissive and complacent. Now the alarm bells are ringing. But as the commentariat pontificates how the US–China tech battle will play out, an equally interesting question to ask is: are there more Chinas out there? Samsung, a South Korean conglomerate, competes with Apple to be the world’s largest manufacturer of smart phones. Arm, founded in the UK, develops chip designs that are used in more than 90% of all mobile devices. Spotify, based in Sweden, is the most popular music streaming service in the world. That’s not all. The world’s most important semiconductor company, TSMC, is in Taiwan. The other most important company in the semiconductor industry, ASML, is in the Netherlands. Some of the world’s best-known games like Minecraft, Candy Crush, and Angry Birds came from gaming studios in the Nordics. Nearly all the major electric battery manufacturers like CATL, LG, and SK On are in Asia. This is a story about technology and the places where it finds its way into the world. Silicon Valley has for half a century been unrivalled in spinning out technologies and fast-growing, high-value, billion-dollar-plus tech companies—the Apples, Facebooks, Googles of the world—that made it the center for the most rapid creation of wealth in human history. Its secrets are spreading to more places. The geography of innovation is shifting. The world has a lot more high-value tech companies than ever before, growing a lot faster than ever before, in a lot more places than ever before. This is a book about these places.

The Global Contest for Breakthrough Technologies

The New Geography of Innovation

As businesses race to unlock the full potential of large language models (LLMs), a critical challenge has emerged: How do you connect these tools to real-time, external data to solve real-world problems? Retrieval-augmented generation (RAG) is the answer. By combining LLMs with information retrieval, RAG empowers you to build everything from intelligent chatbots to autonomous, task-solving agents. Packed with over 70 practical recipes, this go-to guide tackles a wide range of GenAI applications through structured hands-on learning. Author Dominik Polzer provides the tools you need to design, implement, and optimize RAG systems for your unique use cases. Whether you're working with simple data retrieval or designing cutting-edge autonomous agents, this cookbook will help you stay ahead of the curve. <ul> <li>Learn core RAG components including embedding, retrieval, and generation techniques </li><li>Understand advanced workflows like semantic-aware chunking and multi-query prompting </li><li>Build custom solutions such as chatbots and autonomous agents for specific data challenges </li><li>Continuously evaluate and optimize systems for accuracy, relevance, and performance
</li></ul>

Practical Recipes from Data Preprocessing to LLM Agents

Rag with Python Cookbook

A dazzling exploration of the phenomenon of prediction betting markets that asks: what happens when democracy becomes another commodity? For many, Donald Trump's decisive election victory over Kamala Harris in 2024 was a shock. Traditional polls had the race on a razor's edge. But, for those with eyes on prediction betting markets, a very different story was being told. In recent years, prediction markets have swept the world, fundamentally changing the nature of the gambling market, and making their youthful pioneers billionaires. Posed as binary 'Yes/No' questions about future events, prediction bets allow any difference of opinion - whether on politics, wars, assassinations or popular culture - to be financialised. But are these markets really a new phenomenon? What does it mean when markets get closer to the truth than the institutions we built to protect us? And what happens when those tasked with safeguarding democracy possess financial stakes in its volatility? From Renaissance Rome, where merchants wagered on papal conclaves, through London coffee house gossip during the Napoleonic Wars, to the Pentagon's ill-fated terrorism futures exchange, The Big Bet describes the full five-hundred-year arc of a permissive regime which no one designed and no one voted for. Drawing on deep expertise, Michael Auerbach examines how these markets are changing our world, and what they mean for the future of our democratic self-governance. Because they are not an anomaly - they are the logical endpoint of a society that has applied market capitalism to every aspect of life. And in a world when everything is a wager and nothing is off limits, knowing where the chips will fall matters more than ever.

Prediction Markets and the Future of Democracy

The Big Bet

Equips legal professionals and stakeholders with a clear, authoritative, and practical guide to the UK legal treatment of digital payments and tokenised assets. The Law of Digital Payments explores the evolving landscape of UK financial law as it adapts to innovations in digital finance. With fintech disrupting traditional models of value exchange, legal professionals must navigate complex regulatory challenges concerning digital wallets, open banking APIs, smart contracts, decentralised finance (DeFi), and the treatment of tokenised assets under common law. This work delves into how UK courts and regulators are addressing these innovations. It provides clarity on the current legal treatment of payment tokens, security tokens, cryptoassets and non-fungible tokens (NFTs). It also investigates the impact of the Financial Services and Markets Act 2023, the Bank of England's stance on central bank digital currencies (CBDCs), and how the Payment Services Regulations and E-Money Regulations are applied to innovative business models. Drawing upon regulatory guidance, case law, and international developments, the book is designed to help practitioners, regulators, academics, and financial institutions understand and navigate the complex intersection of law and digital finance. This title is included in Bloomsbury Professional's Banking and Finance Law online service.

The Law of Digital Payments

This book is a complete, hands-on guide to designing, training, and deploying your own Large Language Models (LLMs)—from the foundations of tokenization to the advanced stages of fine-tuning and reinforcement learning. Written for developers, data scientists, and AI practitioners, it bridges core principles and state-of-the-art techniques, offering a rare, transparent look at how modern transformers truly work beneath the surface.
Starting from the essentials, you’ll learn how to set up your environment with Python and PyTorch, manage datasets, and implement critical fundamentals such as tensors, embeddings, and gradient descent. You’ll then progress through the architectural heart of modern models, covering RMS normalization, rotary positional embeddings (RoPE), scaled dot-product attention, Grouped Query Attention (GQA), Mixture of Experts (MoE), and SwiGLU activations, each explored in depth and built step by step in code. As you advance, the book introduces custom CUDA kernel integration, teaching you how to optimize key components for speed and memory efficiency at the GPU level—an essential skill for scaling real-world LLMs. You’ll also gain mastery over the phases of training that define today’s leading models:
<ul>
<li>Pretraining - Building general linguistic and semantic understanding.

</li><li>Midtraining - Expanding domain-specific capabilities and adaptability.

</li><li>Supervised Fine-Tuning (SFT) - Aligning behavior with curated, task-driven data.

</li><li>Reinforcement Learning from Human Feedback (RLHF) - Refining responses through reward-based optimization for human alignment.



The final chapters guide you through dataset preparation, filtering, deduplication, and training optimization, culminating in model evaluation and real-world prompting with a custom TokenGenerator for text generation and inference.
By the end of this book, you’ll have the knowledge and confidence to architect, train, and deploy your own transformer-based models, equipped with both the theoretical depth and practical expertise to innovate in the rapidly evolving world of AI.
What You’ll Learn
<ul>
<li>How to configure and optimize your development environment using PyTorch

</li><li>The mechanics of tokenization, embeddings, normalization, and attention mechanisms.

</li><li>How to implement transformer components like RMSNorm, RoPE, GQA, MoE, and SwiGLU from scratch.

</li><li>How to integrate custom CUDA kernels to accelerate transformer computations.

</li><li>The full LLM training pipeline: pretraining, midtraining, supervised fine-tuning, and RLHF.

</li><li>Techniques for dataset preparation, deduplication, model debugging, and GPU memory management.

</li><li>How to train, evaluate, and deploy a complete GPT-like architecture for real-world tasks.





Who this book is for:
Software developers, data scientists, machine learning engineers and AI enthusiasts looking to build their models from scratch.
</li></ul></li></ul>

Design, Train, and Deploy LLMs with PyTorch

Building Large Language Models from Scratch

Business Forecasting unter Einsatz von Machine Learning und Business Intelligence

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