Search results for "Python for Generative AI"
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Introduction to Python for Science and Engineering
Introduction to Python for Science and Engineering offers a quick and incisive introduction to the Python programming language for use in any science or engineering discipline. The approach is pedagogical and “bottom up,” which means starting with examples and extracting more general principles from that experience. No prior programming experience is assumed.Readers will learn the basics of Python syntax, data structures, input and output, conditionals and loops, user-defined functions, plotting, animation, and visualization. They will also learn how to use Python for numerical analysis, including curve fitting, random numbers, linear algebra, solutions to nonlinear equations, numerical integration, solutions to differential equations, and fast Fourier transforms.Readers learn how to interact and program with Python using JupyterLab and Spyder, two simple and widely used integrated development environments.All the major Python libraries for science and engineering are covered, including NumPy, SciPy, Matplotlib, and Pandas. Other packages are also introduced, including Numba, which can render Python numerical calculations as fast as compiled computer languages such as C but without their complex overhead.
R 2,429.09
Predictive Analytics and Generative AI for Data-Driven Marketing Strategies
The book provides an in-depth exploration of cutting-edge technologies and how they are used to support data-driven marketing strategies and empower organizations to make the right decisions. It includes real-world case studies and examples from diverse marketing domains, demonstrating how predictive analytics and generative AI have been successfully applied to solve marketing challenges and drive tangible results. It showcases emerging trends in predictive analytics and generative AI for marketing, and potential impact on the future of data-driven marketing. This book is meant for professionals and scholars to gather the skills and resources to effectively use predictive analytics and generative AI for marketing strategies.• Examines the different predictive analytics models and algorithms, such as regression analysis, decision trees, and neural networks, and demonstrates how they may be utilized to get insightful conclusions from marketing data.• Includes generative AI techniques such as generative adversarial networks (GANs) and variational autoencoders (VAEs), showcasing how these techniques can generate synthetic data for marketing insights and decision-making.• Highlights the importance of data-driven marketing choices and illustrates how generative AI and predictive analytics may be quite useful in this context.• Integrates the principles of data science with marketing concepts, offering a cohesive understanding of how predictive analytics and generative AI can power data-driven marketing decisions.• Present the recent advances in predictive analytics and generative AI, discuss how they can affect the area of data-driven marketing.
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Applied Machine Learning and AI for Engineers
While many introductory guides to AI are calculus books in disguise, this one mostly eschews the math. Instead, author Jeff Prosise helps engineers and software developers build an intuitive understanding of AI to solve business problems. Need to create a system to detect the sounds of illegal logging in the rainforest, analyze text for sentiment, or predict early failures in rotating machinery? This practical book teaches you the skills necessary to put AI and machine learning to work at your company. Applied Machine Learning and AI for Engineers provides examples and illustrations from the AI and ML course Prosise teaches at companies and research institutions worldwide. There's no fluff and no scary equations--just a fast start for engineers and software developers, complete with hands-on examples. This book helps you: Learn what machine learning and deep learning are and what they can accomplishUnderstand how popular learning algorithms work and when to apply themBuild machine learning models in Python with Scikit-Learn, and neural networks with Keras and TensorFlowTrain and score regression models and binary and multiclass classification modelsBuild facial recognition models and object detection modelsBuild language models that respond to natural-language queries and translate text to other languagesUse Cognitive Services to infuse AI into the apps that you write
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R 458.00
Python Debugging for AI, Machine Learning, and Cloud Computing
This book is for those who wish to understand how Python debugging is and can be used to develop robust and reliable AI, machine learning, and cloud computing software. It will teach you a novel pattern-oriented approach to diagnose and debug abnormal software structure and behavior.The book begins with an introduction to the pattern-oriented software diagnostics and debugging process that, before performing Python debugging, diagnoses problems in various software artifacts such as memory dumps, traces, and logs. Next, you’ll learn to use various debugging patterns through Python case studies that model abnormal software behavior. You’ll also be exposed to Python debugging techniques specific to cloud native and machine learning environments and explore how recent advances in AI/ML can help in Python debugging. Over the course of the book, case studies will show you how to resolve issues around environmental problems, crashes, hangs, resource spikes, leaks, and performance degradation. This includes tracing, logging, and analyziing memory dumps using native WinDbg and GDB debuggers. Upon completing this book, you will have the knowledge and tools needed to employ Python debugging in the development of AI, machine learning, and cloud computing applications.What You Will LearnEmploy a pattern-oriented approach to Python debugging that starts with diagnostics of common software problemsUse tips and tricks to get the most out of popular IDEs, notebooks, and command-line Python debuggingUnderstand Python internals for interfacing with operating systems and external modulesPerform Python memory dump analysis, tracing, and loggingWho This Book Is ForSoftware developers, AI/ML engineers, researchers, data engineers, as well as MLOps and DevOps professionals.
R 1,140.00
Machine Learning and Generative AI in Smart Healthcare
The healthcare landscape is constantly evolving, and one of the most significant concerns that healthcare professionals deal with is understanding how to use biomedical intelligence to improve patient outcomes. With the increasing complexity of healthcare computing systems, including technologies like deep learning and the Internet of Things, it can be challenging to navigate these advancements. Machine Learning and Generative AI in Smart Healthcare is a practical tool for healthcare professionals, researchers, and policymakers who are seeking to implement biomedical intelligence solutions. It provides a clear roadmap for using prescriptive and predictive analytics in machine learning to enhance healthcare outcomes. Going beyond the basics, it delves into healthcare computing and networking complexities. By delving into topics such as data mining, disease prediction, and AI applications, deep learning approaches, decision support systems, and optimization techniques, this book equips readers with the practical knowledge they need to optimize healthcare delivery and management.
R 12,356.31
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Deep Dive into the Power Platform in the Age of Generative AI
Understand the full potential of Microsoft Power Platform with this comprehensive guide, designed to provide you with the knowledge and tools needed to create intelligent business applications, automate workflows, and drive data-driven insights for business growth. Whether you're a novice or an experienced professional, this book offers a step-by-step approach to mastering the Power Platform. This book comes with an extensive array of essential concepts, architectural patterns and techniques. It will also guide you with practical insights to navigate the Power Platform effortlessly while integrating on Azure. Starting with exploring Power Apps for building enterprise applications, the book delves into Dataverse, Copilot Studio, AI Builder, managing platforms and Application life cycle management. You will then demonstrate testing strategy followed by a detailed examination of Dataverse and intelligent AI-powered Applications. Additionally, you will cover Power pages for external websites and AI-infused solutions. Each section is meticulously structured, offering step-by-step guidance, hands-on exercises, and real-world scenarios to reinforce learning.After reading the book, you will be able to optimize your utilization of the Power Platform for creating effective business solutions.What You Will Learn:Understand the core components and capabilities of Power PlatformExplore how Power Platform integrates with Azure servicesUnderstand the key features and benefits of using Power Platform for business applicationsDiscover best practices for governance to ensure compliance and efficient managementExplore techniques for optimizing the performance of data integration and export processes on AzureWho This Book Is For:Application developers, Enterprise Architects and business decision-makers.
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Introduction to Python for Science and Engineering
Introduction to Python for Science and Engineering offers a quick and incisive introduction to the Python programming language for use in any science or engineering discipline. The approach is pedagogical and “bottom up,” which means starting with examples and extracting more general principles from that experience. No prior programming experience is assumed.Readers will learn the basics of Python syntax, data structures, input and output, conditionals and loops, user-defined functions, plotting, animation, and visualization. They will also learn how to use Python for numerical analysis, including curve fitting, random numbers, linear algebra, solutions to nonlinear equations, numerical integration, solutions to differential equations, and fast Fourier transforms.Readers learn how to interact and program with Python using JupyterLab and Spyder, two simple and widely used integrated development environments.All the major Python libraries for science and engineering are covered, including NumPy, SciPy, Matplotlib, and Pandas. Other packages are also introduced, including Numba, which can render Python numerical calculations as fast as compiled computer languages such as C but without their complex overhead.
R 6,893.02
R 855.00
R 519.00
R 916.00
R 611.00
Impacts of Generative AI on Creativity in Higher Education
Many educators in the realm of higher education face the critical challenge of fostering creativity in students using traditional teaching methods. In today's rapidly evolving world, these methods have become inadequate to nurture the innovative thinking demanded by modern society. Impacts of Generative AI on Creativity in Higher Education reveals a solution in the integration of generative AI into higher education. To revolutionize how we nurture and harness student creativity, the book explores the intersection of creativity, generative AI, and higher education with a fresh perspective and practical guidance for educators and institutions. It delves into the fundamental concepts of generative AI and its potential applications, providing educators with the tools to create more engaging and innovative learning environments. This book comprehensively examines the role of generative AI in higher education to inspire interdisciplinary collaboration and dialogue among researchers and educators. It offers novel pedagogical approaches that leverage generative AI to foster creativity and provides a roadmap for the future of education. This timely publication is essential reading for educators, students, scholars, and managers looking to understand and harness the transformative power of generative AI in higher education.
R 11,817.13
