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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

India Studies in Business and Economics

This book presents a comprehensive study that conducts a data-driven performance benchmarking exercise for regional school education systems in India, with a clear focus on highlighting disparities and challenges within these systems, as well as providing targeted policy recommendations for potential improvements. The book conducts an in-depth examination of the educational environment, current status, policies, and interventions across schools. It explores why, despite various national initiatives aimed at improving access to and quality of school education, significant gaps persist across Indian states, particularly in the two most populous states, Uttar Pradesh and Bihar, which face a range of economic challenges.The book evaluates rankings and efficiency variations in school education development and develops a novel nonparametric efficiency-effectiveness framework to analyze the performance of the school education system. In addition to employing a state-of-the-art meta-BoD-RDM framework for constructing a school education development index, the empirical analysis employs a two-stage network Data Envelopment Analysis (NDEA) model using survey-based data from schools in India to compute school-wise efficiency and effectiveness scores. These scores are then integrated with a machine learning-based Random Forest algorithm to identify the key factors behind the observed inter-school variations in school efficiency and school effectiveness. The book also discusses progress in school education development during the COVID-19 pandemic. It identifies several key areas that require policy intervention and urgent attention from educationists and governments. This data-enabled benchmarking and analytical study not only contributes to understanding the current landscape but also supports the formulation of future educational policies aimed at effectively addressing the evolving needs of the school education system in India.

Data-Driven Benchmarking of School Education Systems in India

How deep learning—from Google Translate to driverless cars to personal cognitive assistants—is changing our lives and transforming every sector of the economy. The deep learning revolution has brought us driverless cars, the greatly improved Google Translate, fluent conversations with Siri and Alexa, and enormous profits from automated trading on the New York Stock Exchange. Deep learning networks can play poker better than professional poker players and defeat a world champion at Go. In this book, Terry Sejnowski explains how deep learning went from being an arcane academic field to a disruptive technology in the information economy. Sejnowski played an important role in the founding of deep learning, as one of a small group of researchers in the 1980s who challenged the prevailing logic-and-symbol based version of AI. The new version of AI Sejnowski and others developed, which became deep learning, is fueled instead by data. Deep networks learn from data in the same way that babies experience the world, starting with fresh eyes and gradually acquiring the skills needed to navigate novel environments. Learning algorithms extract information from raw data; information can be used to create knowledge; knowledge underlies understanding; understanding leads to wisdom. Someday a driverless car will know the road better than you do and drive with more skill; a deep learning network will diagnose your illness; a personal cognitive assistant will augment your puny human brain. It took nature many millions of years to evolve human intelligence; AI is on a trajectory measured in decades. Sejnowski prepares us for a deep learning future.

The Deep Learning Revolution

The vast potential of AI technology remains untapped in areas like audio, video, and complex data analysis. In fact, many of today's professionals find it challenging to apply AI innovations across these diverse domains due to a lack of guidance and practical implementations.This comprehensive guide, tailored especially for intermediate to advanced ML engineers, data scientists, and researchers, fills the gap. Author Nicole Koenigstein guides readers through the versatile applications of transformer models, not only deepening theoretical understanding but also emphasizing actionable strategies for real-world applications. The book equips you with a grand unified theory for transformers--foundational insights that keep you on the cutting edge regardless of state-of-the-art model evolutions. You'll discover how to apply: <ul><li>Transformers in nontext domains like image, video, and music generation</li> <li>Reasoning models, coding agents, and multi-agent architectures</li> <li>Training-time and test-time optimization strategies</li> <li>Production deployment, runtime engineering, and hardware efficiency</li></ul>

Applications Beyond Nlp

Transformers: The Definitive Guide

Inventory Optimization

This book serves as an essential guide for both beginners and advanced learners in the field of inventory control and supply chain management. It meticulously presents the fundamental terminologies, models, and theories necessary for understanding and mastering these subjects. What sets this book apart is its incorporation of modern, updated methods rooted in probability theory and fuzzy logic, offering readers a deeper insight into the complexities of inventory and supply chain issues. Instead of focusing solely on contemporary advancements, this book explores a wide range of inventory and supply chain problems, utilizing fuzzy logic to provide innovative solutions. It thoroughly integrates the latest developments in the field, ensuring readers are equipped with the most current knowledge. Ideal for beginners, professionals, and researchers alike, this book offers a comprehensive, up-to-date resource for tackling inventory and supply chain challenges effectively.

Innovative Approaches to Inventory Control and Supply Chain Management

This innovative textbook edited by international experts in technology law and policy provides a comprehensive and accessible guide into the fast-evolving landscape of technology law and policy in the UK and the EU. The recent wave of regulatory reforms adopted by UK and EU regulators increases the complexity of Internet law as it had developed in the past decades. Recognising the ever-growing importance of artificial intelligence in today's public discourse, the textbook extends beyond traditional legal sectoral frameworks, and explores the intersection of law, technology, and public policy to describe and critically reflect on current and emerging issues in the modern information society. As well as providing accessible guides to how law and policy came to be made in relation to topics like platform liability, AI, copyright, and privacy and data protection, the book also homes in on key areas such as the EU AI Act, adtech regulation, social media, chatbots, the gig worker economy, cybersecurity and predictive policing." The companion website provides multimedia resources to delve deeper into specific topics; introductory materials for readers that are unfamiliar with the EU legal system; and teaching resources. Law, Policy, and the Internet is an essential resource for anyone seeking to navigate the complexities of internet regulation in an era of exponential technological change.

Law, Policy and the Internet

HBR's 10 Must Reads

How to stay ahead in a world transformed by AI.If you read nothing else on artificial intelligence, read this book. We've chosen a new selection of current and classic Harvard Business Review articles that will help you make sense of the evolving generative AI landscape, manage regulation and risk, and develop a strategy that keeps pace with technological change.This book will inspire you to: <ul><li>Help your people and technology work better together</li><li>Redesign roles, workflows, and capabilities</li><li>Keep your AI projects on track</li><li>Address gen AI's quality control and waste problems</li><li>Harness the potential of agentic AI</li><li>Embed AI in the core of your business</li></ul>This collection of articles includes "For Success with AI, Bring Everyone on Board," by David De Cremer; "Bring Human Values to AI," by Jacob Abernethy, Francois Candelon, Theodoros Evgeniou, Abhishek Gupta, and Yves Lostanlen; "From Prediction to Transformation," by Ajay Agrawal, Joshua Gans, and Avi Goldfarb; "How AI Can Help Managers Think Through Problems," by Elisa Farri and Gabriele Rosani; "The Gen AI Playbook for Organizations," by Bharat N. Anand and Andy Wu; "Agentic AI Is Already Changing the Workforce," by Jen Stave, Ryan Kurt, and John Winsor; "Keep Your AI Projects on Track," by Iavor Bojinov; "How to Marry Process Management and AI," by Thomas H. Davenport and Thomas C. Redman; "The Hidden Penalty of Using AI at Work," by Oguz A. Acar, Phyliss Jia Gai, Yanping Tu, and Jiayi Hou; "Heavy Machinery Meets AI," by Vijay Govindarajan and Venkat Venkatraman; "AI Is Changing the Structure of Consulting Firms," by David S. Duncan, Tyler Anderson, and Jeffrey Saviano; "Stop Running So Many AI Pilots," by Goutam Challagalla, Mahwesh Khan, and Fabrice Beaulieu; "Addressing Gen AI's Quality-Control Problem," by Stefan Thomke, Philipp Eisenhauer, and Puneet Sahni; "AI's Growing Waste Problem--and How to Solve It," by Samsurin Welch, Khaled Soufani, and Eva Morales; and "Don't Let an AI Failure Harm Your Brand," by Julian De Freitas.HBR's 10 Must Reads are definitive collections of classic ideas, practical advice, and essential thinking from the pages of Harvard Business Review. Exploring topics like disruptive innovation, emotional intelligence, and new technology in our ever-evolving world, these books empower any leader to make bold decisions and inspire others.This Updated and Expanded edition features new, breakthrough articles, additional short-form pieces, and a detailed discussion guide to give you and your team the tools you need for sustained success.

HBR's 10 Must Reads on Artificial Intelligence

The Triple Intelligence Framework

Data-Driven Sustainable Workforce Analytics

Platform Supply Chains in the AI Era

Risk Management

Platform Supply Chains 5

What AI Can’t Do Without You

The Human Advantage

'Engaging, insightful, panoramic' Mustafa Suleyman, CEO of Microsoft AI &amp; Cofounder of DeepMind 'An eye-opening exploration of a revolution unfolding before our eyes' New York Journal of Books Stunning advances in digital technology have introduced a new wave of human-like AI systems. Chatbots like ChatGPT, Claude, and Gemini are already reshaping economies, challenge democracies, and reshaping society in unpredictable ways. And soon, these AI systems could make autonomous decisions on their users' behalf, transforming everything we do. Understanding how they work is crucial. Can AI systems think, know, and understand?Could they manipulate or deceive you, and if so, what might they make you do? Whose interests do they represent? When will they be able to move beyond words and take action in the real world? Neuroscientist and AI researcher Christopher Summerfield explores these questions, charting AI's evolution from early ideas in the seventeenth century to today's deep neural networks. His book is the most accessible, up-to-date, and authoritative exploration of this radical technology. With an understanding of AI's inner workings, we can address the existential question of our age: can we look forward to a technological utopia, or are we writing ourselves out of history? 'As a leading authority...Summerfield is perfectly situated to explore the meaning and implications of these machines that are so uncannily like - and unlike - ourselves' Brian Christian, co-author of Algorithms to Live by 'You might choose to be alarmed, excited, or indifferent to LLMs, but you should read Chris's book before you decide' Mike Woolridge, author of The Road to Conscious Machines

How AI Learned to Talk and What It Means

These Strange New Minds

This book helps sales professionals, support teams, process improvement experts, and internal consultants to reduce operational complexity to improve sales operations. In addition to proven process methodologies, it discusses how to integrate leading-edge technologies, such as Artificial Intelligence (AI), work task mining, digitalization, and data governance to reduce process complexity and friction.It is estimated that salespeople spend less than 50% of their time selling products or services. For some organizations, this percentage is as low as 30%. Non-selling time is spent on administrative activities and prospecting for new customers. Administrative activities include sales reporting, expediting orders for different reasons, handling customer inquiries and complaints, training, and working through many tools, processes, and teams needed to get information or work done. The goal of this book is to show ways to remove administrative work tasks from sellers to increase deal velocity, give back selling time, and reduce lead time from quote to cash.In parallel, the author discusses ways to automate these tasks using automation strategies, including AI for important work tasks, such as prospecting, lead management, creating quotes and proposals, preparing and managing customer meetings, and similar work. This book enhances customer, sales, support teams, and stakeholder satisfaction.

How to Use Artificial Intelligence and Digitalization Applications to Improve Processes

Sales Support Operations

mitp Professional

<ul><li>KI-Programmierung leicht gemacht - praktische Projekte ohne überflüssige Mathematik</li>
<li>Einsatz mächtiger Bibliotheken wie TensorFlow, SpaCy und music21 - auch ohne Vorkenntnisse in Python</li>
<li>Mit Programmieraufgaben, Bildern zur Veranschaulichung, Übungsfragen und vielen Anregungen zum Ausprobieren</li></ul>


Starte direkt mit echten KI-Projekten
Mit diesem Buch startest du direkt durch: Du lernst künstliche Intelligenz, indem du selbst programmierst - praxisnah, kreativ und verständlich. Schritt für Schritt entwickelst du spannende KI-Anwendungen mit wenigen Codezeilen: vom Chatbot über Bilderkennung bis hin zur Musik- und Bildgenerierung. Du experimentierst mit maschinellem Lernen und verstehst, wie lernende Systeme wirklich funktionieren. Alles, was du brauchst, sind grundlegende Programmierkenntnisse.

Alles dabei - von den Python-Grundlagen bis zu modernen KI-Bibliotheken
Dank klarer Erklärungen und anschaulicher Beispiele findest du dich auch als Einsteiger schnell zurecht. Du lernst alle wichtigen Techniken kennen und setzt sie direkt um - von einfachen Klassifikationsmodellen bis hin zu generativer KI mit GANs, RNNs und Diffusionsmodellen. Dabei nutzt du professionelle Bibliotheken wie NumPy, TensorFlow, Matplotlib, SpaCy und music21.

Programmieren, verstehen, experimentieren
Jedes Kapitel lädt zum Mitmachen ein - mit abwechslungsreichen Aufgaben, anschaulichen Abbildungen und vielen Ideen zum Ausprobieren. Du lernst, wie du KIs mit eigenen Daten trainierst oder Daten aus dem Internet nutzt, um spannende Anwendungen zu entwickeln. Die Programme kannst du entweder lokal auf deinem Rechner umsetzen oder du arbeitest im Browser mit Google Colab.

Aus dem Inhalt:
<ul><li>Grundlagen der künstlichen Intelligenz</li>
<li>Generative und diskriminierende KI</li>
<li>KI programmieren mit Python-Bibliotheken:
<ul><li>NumPy</li>
<li>Matplotlib</li>
<li>TensorFlow</li>
<li>SpaCy</li>
<li>music21</li></ul>
</li><li>Sprachmodelle und Natural Language Processing</li>
<li>Überwachtes, unüberwachtes und Verstärkungslernen</li>
<li>Künstliche neuronale Netze</li>
<li>Bildgenerierung mit GAN und CNN</li>
<li>Text erzeugen mit RNN und LSTM</li>
<li>Musik komponieren mit music21</li>
<li>Zahlreiche Aufgaben mit Lösungen</li>
</ul>

Dein einfacher Einstieg - Generative KI, Chatbots, Objekterkennung & Co

KI-Projekte mit Python

Business Forecasting unter Einsatz von Machine Learning und Business Intelligence

Autres titres sur ce thème