mercury learning and information de gruyter jan 2025 (8 Ergebnisse)

Taschenbuch. Zustand: Neu. Neuware -This book is a comprehensive guide designed to teach the fundamentals of Python programming while introducing the exciting possibilities of Generative AI. Whether you re a novice or a developer looking to integrate Grok into your workflow, this book offers a clear, step-by-step path to mastering Python and leveraging AI-driven code generation.Walter de Gruyter GmbH, Genthiner Strasse 13, 10785 Berlin 310 pp. Englisch.

Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - An updated history of classical philology had long been a desideratum of scholars of the ancient world. The volume edited by Diego Lanza and Gherardo Ugolini is structured in three parts. In the first one ('Towards a science of antiquity') the approach of Anglo-Saxon philology (R. Bentley) and the institutionalization of the discipline in the German academic world (C.G. Heyne and F.A. Wolf) are described. In the second part ('The illusion of the archetype. Classical Studies in the Germany of the 19th Century') the theoretical contributions and main methodological disputes that followed are analysed (K. Lachmann, J.G. Hermann, A. Boeckh, F. Nietzsche and U. von Wilamowitz-Moellendorff). The last part ('The classical philology of the 20th century') treats the redefinition of classical studies after the Great War in Germany (W. Jaeger) and in Italy (G. Pasquali). In this context, the contributions of papyrology and of the new images of antiquity that have emerged in the works of writers, narrators, and translators of our time have been considered. This part finishes with the presentation of some of the most influential scholars of the last decades (B. Snell, E.R. Dodds, J.-P. Vernant, B. Gentili, N. Loraux).

Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book is a comprehensive guide to aligning your marketing strategies with business objectives while embracing the latest innovations in data and AI-driven analytics. You'll cover topics such as: aligning measurement to business goals by distinguishing between business and marketing KPIs and choosing the right metrics to guide your strategy; building adaptable systems that link organizational goals to actionable marketing tactics; exploring AI-based tools, predictive analytics, and generative AI to refine your data strategies; and analyzing results, run multi-channel tests, and create a culture of experimentation and optimization. Through a unique blend of expert insights, practical frameworks, and a recurring case study, this book brings theoretical concepts to life, making them actionable and relatable for any organization.FEATURES¿ Integrates cutting-edge AI technologies into your measurement processes¿ Uses a recurring case study to demonstrate real-world applications of measurement concepts¿ Analyzes results and runs multi-channel tests to create a culture of experimentation and optimizationWalter de Gruyter, Genthiner Straße 13, 10785 Berlin 270 pp. Englisch.

Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Data Science for Decision Makers is an essential guide for executives, managers, entrepreneurs, and anyone seeking to harness the power of data to drive business success. In today's fast-paced and increasingly digital world, the ability to make informed decisions based on data-driven insights is vital. This book serves as a bridge between the complex world of data science and the strategic decision-making process, providing readers with the knowledge and tools they need to leverage data effectively.With a clear focus on practical application, this book demystifies key concepts in data science, from data collection and analysis to predictive modeling and visualization. Via real-world examples, case studies, and actionable insights, readers will learn how to extract insights from data and translate them into actionable strategies that drive organizational growth.Written in a reader-friendly manner, this book caters to both novice and experienced professionals alike. Whether you're a seasoned executive looking to sharpen your strategic acumen or a manager seeking to enhance your team's data literacy, this essential reference provides the necessary foundation to navigate the complex landscape of data science with confidence.Walter de Gruyter, Genthiner Straße 13, 10785 Berlin 196 pp. Englisch.

Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book will introduce essential concepts in financial analysis methods & models, covering time-series analysis, graphical analysis, technical and fundamental analysis, asset pricing and portfolio theory, investment and trade strategies, risk assessment and prediction, and financial ML practices. The Python programming language and its ecosystem libraries, such as Pandas, NumPy, SciPy, statsmodels, Matplotlib, Seaborn, Scikit-learn, Prophet, and other data science tools will demonstrate these rooted financial concepts in practice examples. This book will also help you understand the concepts of financial market dynamics, estimate the metrics of financial asset profitability, predict trends, evaluate strategies, optimize portfolios, and manage financial risks. You will also learn data analysis techniques using the Python programming language to understand the basics of data preparation, visualization, and manipulation in the world of financial data.FEATURES- Illustrates financial data analysis using Python data science libraries & techniques- Uses Python visualization tools to justify investment and trading strategies- Covers asset pricing & portfolio management methods with Python 504 pp. Englisch.

Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book will introduce essential concepts in financial analysis methods & models, covering time-series analysis, graphical analysis, technical and fundamental analysis, asset pricing and portfolio theory, investment and trade strategies, risk assessment and prediction, and financial ML practices. The Python programming language and its ecosystem libraries, such as Pandas, NumPy, SciPy, statsmodels, Matplotlib, Seaborn, Scikit-learn, Prophet, and other data science tools will demonstrate these rooted financial concepts in practice examples. This book will also help you understand the concepts of financial market dynamics, estimate the metrics of financial asset profitability, predict trends, evaluate strategies, optimize portfolios, and manage financial risks. You will also learn data analysis techniques using the Python programming language to understand the basics of data preparation, visualization, and manipulation in the world of financial data.FEATURES¿ Illustrates financial data analysis using Python data science libraries & techniques¿ Uses Python visualization tools to justify investment and trading strategies¿ Covers asset pricing & portfolio management methods with PythonWalter de Gruyter, Genthiner Straße 13, 10785 Berlin 504 pp. Englisch.

Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -In today's data-driven world, the ability to analyze and interpret data is no longer optional-it's a necessity for making informed business decisions. This book provides a comprehensive, hands-on guide to mastering the essential techniques and tools that empower business analysts to transform raw data into actionable insights. Packed with practical exercises and real-world case studies, this book focuses on applying statistical methods across the most widely used tools, including Excel, R, Python, and generative AI platforms like ChatGPT. Key topics include framing analytical questions, descriptive and advanced statistical techniques, text analytics and A/B testing, and big data and visualization. Whether analyzing sales trends, optimizing marketing strategies, or improving operational efficiency, you'll gain the skills to make data-backed decisions that drive business success.FEATURES¿ Includes hands-on exercises with industry-standard tools, including Excel, R, Python, and generative AI¿ Covers step-by-step instructions for advanced techniques like time series forecasting and contingency analysis¿ Uses real-world case studies to demonstrate the application of concepts to business scenarios¿ Features companion files with datasets, surveys, and cases (available for downloading from the publisher)Walter de Gruyter, Genthiner Straße 13, 10785 Berlin 440 pp. Englisch.

Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book offers a thorough exploration of Large Language Models (LLMs), guiding developers through the evolving landscape of generative AI and equipping them with the skills to utilize LLMs in practical applications. Designed for developers with a foundational understanding of machine learning, this book covers essential topics such as prompt engineering techniques, fine-tuning methods, attention mechanisms, and quantization strategies to optimize and deploy LLMs. Beginning with an introduction to generative AI, the book explains distinctions between conversational AI and generative models like GPT-4 and BERT, laying the groundwork for prompt engineering (Chapters 2 and 3). Some of the LLMs that are used for generating completions to prompts include Llama-3.1 405B, Llama 3, GPT-4o, Claude 3, Google Gemini, and Meta AI. Readers learn the art of creating effective prompts, covering advanced methods like Chain of Thought (CoT) and Tree of Thought prompts. As the book progresses, it details fine-tuning techniques (Chapters 5 and 6), demonstrating how to customize LLMs for specific tasks through methods like LoRA and QLoRA, and includes Python code samples for hands-on learning. Readers are also introduced to the transformer architecture's attention mechanism (Chapter 8), with step-by-step guidance on implementing self-attention layers. For developers aiming to optimize LLM performance, the book concludes with quantization techniques (Chapters 9 and 10), exploring strategies like dynamic quantization and probabilistic quantization, which help reduce model size without sacrificing performance.FEATURES¿ Covers the full lifecycle of working with LLMs, from model selection to deployment¿ Includes code samples using practical Python code for implementing prompt engineering, fine-tuning, and quantization¿ Teaches readers to enhance model efficiency with advanced optimization techniques¿ Includes companion files with code and images -- available from the publisherWalter de Gruyter, Genthiner Straße 13, 10785 Berlin 1046 pp. Englisch.