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Machine Learning and Generative AI for Marketing
Start transforming your data-driven marketing strategies and increasing customer engagement. Learn how to create compelling marketing content using advanced gen AI techniques and stay in touch with the future AI ML landscape.Purchase of the print or Kindle book includes a free eBook in PDF formatKey FeaturesEnhance customer engagement and personalization through predictive analytics and advanced segmentation techniquesCombine Python programming with the latest advancements in generative AI to create marketing content and address real-world marketing challengesUnderstand cutting-edge AI concepts and their responsible use in marketingBook DescriptionIn the dynamic world of marketing, the integration of artificial intelligence (AI) and machine learning (ML) is no longer just an advantage—it's a necessity. Moreover, the rise of generative AI (GenAI) helps with the creation of highly personalized, engaging content that resonates with the target audience.This book provides a comprehensive toolkit for harnessing the power of GenAI to craft marketing strategies that not only predict customer behaviors but also captivate and convert, leading to improved cost per acquisition, boosted conversion rates, and increased net sales.Starting with the basics of Python for data analysis and progressing to sophisticated ML and GenAI models, this book is your comprehensive guide to understanding and applying AI to enhance marketing strategies. Through engaging content & hands-on examples, you'll learn how to harness the capabilities of AI to unlock deep insights into customer behaviors, craft personalized marketing messages, and drive significant business growth. Additionally, you'll explore the ethical implications of AI, ensuring that your marketing strategies are not only effective but also responsible and compliant with current standardsBy the conclusion of this book, you'll be equipped to design, launch, and manage marketing campaigns that are not only successful but also cutting-edge.What you will learnMaster key marketing KPIs with advanced computational techniquesUse explanatory data analysis to drive marketing decisionsLeverage ML models to predict customer behaviors, engagement levels, and customer lifetime valueEnhance customer segmentation with ML and develop highly personalized marketing campaignsDesign and execute effective A/B tests to optimize your marketing decisionsApply natural language processing (NLP) to analyze customer feedback and sentimentsIntegrate ethical AI practices to maintain privacy in data-driven marketing strategiesWho this book is forThis book targets a diverse group of professionals:Data scientists and analysts in the marketing domain looking to apply advanced AI ML techniques to solve real-world marketing challengesMachine learning engineers and software developers aiming to build or integrate AI-driven tools and applications for marketing purposesMarketing professionals, business leaders, and entrepreneurs who must understand
R 1,693.00
Generative AI for Marketing
Every few generations, a technoeconomic revolution topples the status quo of how work is done, creating an opportunity for new leaders to emerge. Generative AI for Marketing is meant to position the current and future marketers to become those leaders and lead their organizations in the AI era.To succeed in leveraging AI, organizations must look beyond practices that were established before the AI era. This book elucidates the evolving role and needs of Generative AI in marketing, providing a blueprint for businesses to thrive in an ever-evolving business landscape by achieving the agility and adaptability needed to sustain growth with AI.Tailored for marketers and business students alike, readers will gain a commanding set of tools to master the trifecta of foundational AI knowledge, its applications in Marketing, and the knowhow to automate growth without increasing costs.
R 873.96
Predictive Analytics and Generative AI for Data-Driven Marketing Strategies
In providing 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, Predictive Analytics and Generative AI for Data-Driven Marketing Strategies includes real-world case studies and examples from diverse marketing domains. This book demonstrates how predictive analytics and generative AI have been successfully applied to solve marketing challenges and drive tangible results. This book showcases emerging trends in predictive analytics and generative AI for marketing, and their potential impact on the future of data-driven marketing. This book is meant for professionals and scholars to gather the skills and resources to use predictive analytics and generative AI effectively for marketing strategies.This book: • 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.• Presents the recent advances in predictive analytics and generative AI and discusses how they can affect the area of data-driven marketing.
R 2,674.00
R 3,339.97
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.
R 9,317.91
AI and Machine Learning Applications in Supply Chains and Marketing
While artificial intelligence (AI) simulates human intelligence in machines, machine learning (ML) enables systems to learn from data without explicit programming. In marketing and supply chain management, AI and ML empower businesses to analyze consumer behavior, personalize experiences, optimize advertising strategies, forecast consumer demands, manage inventory, plan routes, and mitigate risks. Businesses can enhance efficiency, accuracy, decision-making, customer engagement, and cost-effectiveness when integrating AI and ML in marketing and supply chain operations. Further research is necessary to drive success in the dynamic marketplace. AI and Machine Learning Applications in Supply Chains and Marketing bridges the gap between theoretical knowledge and practical application of AI and ML in marketing and supply chain management. It examines emerging technologies that can revolutionize industries by transforming business operations. This book covers topics such as data analysis, sustainable development, and blockchain, and is a useful resource for business owners, economists, marketing professionals, engineers, computer scientists, academicians, and researchers.
R 10,069.15
Google Machine Learning and Generative AI for Solutions Architects
Architect and run real-world AI/ML solutions at scale on Google Cloud, and discover best practices to address common industry challenges effectivelyKey FeaturesUnderstand key concepts, from fundamentals through to complex topics, via a methodical approachBuild real-world end-to-end MLOps solutions and generative AI applications on Google CloudGet your hands on a code repository with over 20 hands-on projects for all stages of the ML model development lifecyclePurchase of the print or Kindle book includes a free PDF eBookBook DescriptionNearly all companies nowadays either already use or are trying to incorporate AI/ML into their businesses. While AI/ML research is undoubtedly complex, the building and running of apps that utilize AI/ML effectively is tougher. This book shows you exactly how to design and run AI/ML workloads successfully using years of experience some of the world’s leading tech companies have to offer.You’ll begin by gaining a clear understanding of essential fundamental AI/ML concepts, before moving on to grasp complex topics with the help of examples and hands-on activities. This will help you eventually explore advanced, cutting-edge AI/ML applications that address real-world use cases in today’s market. As you advance, you’ll recognize the common challenges that companies face when implementing AI/ML workloads, and discover industry-proven best practices to overcome these challenges. The chapters also teach you about the vast AI/ML landscape on Google Cloud and how to implement all the steps needed in a typical AI/ML project. You’ll use services such as BigQuery to prepare data; Vertex AI to train, deploy, monitor, and scale models in production; as well as MLOps to automate the entire process.By the end of this book, you will be able to unlock the full potential of Google Cloud's AI/ML offerings.What you will learnBuild solutions with open-source offerings on Google Cloud, such as TensorFlow, PyTorch, and SparkSource, understand, and prepare data for ML workloadsBuild, train, and deploy ML models on Google CloudCreate an effective MLOps strategy and implement MLOps workloads on Google CloudDiscover common challenges in typical AI/ML projects and get solutions from expertsExplore vector databases and their importance in Generative AI applicationsUncover new Gen AI patterns such as Retrieval Augmented Generation (RAG), agents, and agentic workflowsWho this book is forThis book is for aspiring solutions architects looking to design and implement AI/ML solutions on Google Cloud. Although this book is suitable for both beginners and experienced practitioners, basic knowledge of Python and ML concepts is required. The book focuses on how AI/ML is used in the real world on Google Cloud. It briefly covers the basics at the beginning to establish a baseline for you, but it does not go into depth on the underlying mathematical concepts that are readily available in academic material.
R 1,693.00
AI Powered Insight
In our hyper-connected world, where every interaction generates valuable data, artificial intelligence (AI) is having a profound impact on marketing, marketing research, and customer data analytics.This book sheds light on the untapped potential of AI-driven analytics in market research so that businesses can better understand and interact with their customers. The transformation of marketing and market research over recent decades has only accelerated thanks to breathtaking AI developments that are reshaping data analytics and insights generation while enabling more effective foresight and actionability.These technologies are moving the field beyond solicited customer opinion, traditionally gathered through surveys and focus groups, allowing marketers to leverage unstructured big data for a whole new type of customer feedback: the unsolicited opinion. Acting as a guide to what’s possible, the book explores the redefinition of insight in the age of AI and stresses the need for every true insight to inspire action. It dives into techniques for analysis and the AI science behind the analytics, automated brand recommendations, and content creation, introducing AI-specific research and data analysis tools. The birth of synthetic data is discussed, with advantages including privacy compliance, cost-effectiveness, and the ability to generate diverse datasets on demand. The book also covers critical ethical issues, such as data privacy, algorithmic bias, transparency, and the potential for AI to be used manipulatively, and raises important questions around knowledge, creativity, and the future of the field of marketing research.This book’s clear-eyed guidance and thoughtful reflections will benefit anyone involved in marketing, market research, digital advertising, and business strategy, including CX practitioners, business leaders tasked with delivering growth, data scientists, marketing agency executives and consultants, and advanced business and marketing students.
R 8,572.00
artificial Intelligence / Machine Learning In Marketing
The theory and practice of AI and ML in marketing saving time, money
R 495.69
R 4,192.07
Practical Guide to Machine Learning, NLP, and Generative AI: Libraries, Algorithms, and Applications
This is an essential resource for beginners and experienced practitioners in machine learning. This comprehensive guide covers a broad spectrum of machine learning topics, starting with an in-depth exploration of popular machine learning libraries. Readers will gain a thorough understanding of Scikit-learn, TensorFlow, PyTorch, Keras, and other pivotal libraries like XGBoost, LightGBM, and CatBoost, which are integral for efficient model development and deployment.The book delves into various neural network architectures, providing readers with a solid foundation in understanding and applying these models. Beginning with the basics of the Perceptron and its application in digit classification, it progresses to more complex structures such as multilayer perceptrons for financial forecasting, radial basis function networks for air quality prediction, and convolutional neural networks (CNNs) for image classification. Additionally, the book covers recurrent neural networks (RNNs) and their variants like long short-term memory (LSTM) and gated recurrent units (GRUs), which are crucial for time-series analysis and sequential data applications.Supervised machine learning algorithms are meticulously explained, with practical examples to illustrate their application. The book covers logistic regression and its use in predicting sports outcomes, decision trees for plant classification, random forests for traffic prediction, and support vector machines for house price prediction. Gradient boosting machines and their applications in genomics, AdaBoost for bioinformatics data classification, and extreme gradient boosting (XGBoost) for churn prediction are also discussed, providing readers with a robust toolkit for various predictive tasks.Unsupervised learning algorithms are another significant focus of the book, introducing readers to techniques for uncovering hidden patterns in data. Hierarchical clustering for gene expression data analysis, principal component analysis (PCA) for climate predictions, and singular value decomposition (SVD) for signal denoising are thoroughly explained. The book also explores applications like robot navigation and network security, demonstrating the versatility of these techniques.Natural language processing (NLP) is comprehensively covered, highlighting its fundamental concepts and various applications. The book discusses the overview of NLP, its fundamental concepts, and its diverse applications such as chatbots, virtual assistants, clinical NLP applications, and social media analytics. Detailed sections on text pre-processing, syntactic analysis, machine translation, text classification, named entity recognition, and sentiment analysis equip readers with the knowledge to build sophisticated NLP models.The final chapters of the book explore generative AI, including generative adversarial networks (GANs) for image generation, variational autoencoders for vibrational encoder training, and autoregressive models for time series
R 2,748.00
Using Generative AI for SEO
Generative AI has brought artificial intelligence into the mainstream. The natural language capabilities of this technology provide digital marketers with exciting new ways to use AI in their day-to-day operations. Yet few SEO practitioners understand how to integrate this capability into their business.Using Generative AI and SEO is the first authoritative book dedicated to helping SEO practitioners effectively integrate generative AI capabilities into their work. No matter where you are in your SEO journey, it's critical to get started so that your organization can gain a competitive advantage. This book provides the necessary background, knowledge, skills, and practical examples to get you working quickly and confidently with this essential new tool.Understand how generative AI can help you impact SEOExplore practical applications you can use right nowLearn the competencies you'll need to ensure your toolkit remains relevantImprove content creation throughput while improving qualityConsider risks and limitations of AI applications in SEOBuild a generative AI capability within your organization
R 912.00
ML and Generative AI in the Data Lakehouse
In today's race to harness generative AI, many teams struggle to integrate these advanced tools into their business systems. While platforms like GPT-4 and Google's Gemini are powerful, they aren't always tailored to specific business needs. This book offers a practical guide to building scalable, customized AI solutions using the full potential of data lakehouse architecture.Author Bennie Haelen covers everything from deploying ML and GenAI models in Databricks to optimizing performance with best practices. In this must-read for data professionals, you'll gain the tools to unlock the power of large language models (LLMs) by seamlessly combining data engineering and data science to create impactful solutions.Learn to build, deploy, and monitor ML and GenAI models on a data lakehouse architecture using DatabricksLeverage LLMs to extract deeper, actionable insights from your business data residing in lakehousesDiscover how to integrate traditional ML and GenAI models for customized, scalable solutionsUtilize open source models to control costs while maintaining model performance and efficiencyImplement best practices for optimizing ML and GenAI models within the Databricks platform
R 1,978.00
Supply Chain Transformation Through Generative AI and Machine Learning
The transformative role of Generative Artificial Intelligence (AI) and Machine Learning (ML) in supply chain management is increasingly being recognized as a game-changer in the industry. Recent statistics underscore this trend, highlighting the rapid adoption and significant impact of these technologies. However, the path to digital transformation is not without its challenges. Despite improved success rates, about 60% of digital transformation initiatives in supply chains still struggle to fully meet their objectives. This shortfall is often attributed to several key factors: the complexity and scale of integrating new technologies into existing systems; organizational resistance to change and inadequate stakeholder buy-in; lack of skilled professionals adept in these new technologies; insufficient data governance and quality; and underestimation of the need for a robust change management strategy. These challenges highlight the critical need for a comprehensive approach that addresses both the technical and human aspects of digital transformation. Supply Chain Transformation Through Generative AI and Machine Learning is a comprehensive resource to the best practices in digital enablement, change management, and process optimization, with a specific focus on Generative AI and ML. It equips readers with the knowledge and strategies necessary for successful integration of these technologies, drawing on the latest industry insights and expert recommendations, to enhance supply chain efficiency and effectiveness, reduce costs, and drive revenue growth. Covering topics such as AI-powered visual models, demand planning, and product clustering, this book is an excellent resource for executives, business leaders, program managers, data scientists, AI and ML developers, industry analysts, consultants, professionals, scholars, researchers, academicians, and more.
R 8,766.62
AI Powered Insight
In our hyper-connected world, where every interaction generates valuable data, artificial intelligence (AI) is having a profound impact on marketing, marketing research, and customer data analytics.This book sheds light on the untapped potential of AI-driven analytics in market research so that businesses can better understand and interact with their customers. The transformation of marketing and market research over recent decades has only accelerated thanks to breathtaking AI developments that are reshaping data analytics and insights generation while enabling more effective foresight and actionability.These technologies are moving the field beyond solicited customer opinion, traditionally gathered through surveys and focus groups, allowing marketers to leverage unstructured big data for a whole new type of customer feedback: the unsolicited opinion. Acting as a guide to what’s possible, the book explores the redefinition of insight in the age of AI and stresses the need for every true insight to inspire action. It dives into techniques for analysis and the AI science behind the analytics, automated brand recommendations, and content creation, introducing AI-specific research and data analysis tools. The birth of synthetic data is discussed, with advantages including privacy compliance, cost-effectiveness, and the ability to generate diverse datasets on demand. The book also covers critical ethical issues, such as data privacy, algorithmic bias, transparency, and the potential for AI to be used manipulatively, and raises important questions around knowledge, creativity, and the future of the field of marketing research.This book’s clear-eyed guidance and thoughtful reflections will benefit anyone involved in marketing, market research, digital advertising, and business strategy, including CX practitioners, business leaders tasked with delivering growth, data scientists, marketing agency executives and consultants, and advanced business and marketing students.
R 1,758.00
R 356.00
Artificial Intelligence and Machine Learning and Marketing Management
OBJECTIVES The book objectives provide a full delivery of information on the fields of artificial intelligence (AI) and machine learning (ML) to educators, students and practitioners of marketing. By explaining AI and ML terminology and its applications including marketing, the book is designed to inform and educate. Marketing use of AI and ML has exploded in recent decades as marketers have seen the considerable benefits of these two technologies. It is understood and explained that AI deals with 'Intelligent behaviour' by machines rather than natural intelligence found in humans and animals, it is the machine mimicking ' cognitive functions' that humans associate with the mind in learning, expression and problem solving and much more.
R 988.33
R 428.00
R 762.00
Exploring Generative AI with Computational Intelligence
This book demystifies the concept of AI-driven creativity with an in-depth understanding of the underlying principles, algorithms, and applications of generative AI. It begins with a coverage of AI fundamentals, followed by a technical discussion including detailed explanations of model architectures, training processes, and optimisation techniques. It explores case studies showcasing how generative AI is reshaping industries such as entertainment, marketing, design, and healthcare. The book also tackles ethical considerations, addressing issues related to bias, transparency, and responsible AI development.Features:Provides deep understanding of generative AI, including in-depth coverage of various generative models such as GANs, VAEs, and RNNs.Includes practical, real-world examples of how generative AI is applied in different industries.Dedicates significant attention to ethical considerations.Equips readers with the knowledge and tools to build, train, and deploy their own generative AI systems.Offers thorough explanations of AI algorithms, neural network architectures, and training processes.This book is aimed at graduate students and researchers in computer engineering, AI and ML.
R 7,584.84
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 16,376.09
Winning Marketing Strategies Using Generative AI
Unlock Brilliant Strategies with AI-Enhanced MarketingDiscover the future of marketing with our comprehensive guide that introduces the MVOSSTE framework. Augmented by cutting-edge generative AI, this book offers a clear roadmap from mis-sion to execution, empowering you to craft innovative and effective marketing strategies. Perfect for marketers eager to stay ahead of the curve, our guide transforms complex concepts into actionable insights for unparalleled success.
R 873.23
ChatGPT for Marketing
Explore the capabilities of ChatGPT and gain insight on how to utilize this AI tool in your daily tasks, and marketing endeavors. This book introduces ChatGPT, covering its architecture, training process, and applications across various fields. Start by delving into the benefits of integrating ChatGPT into everyday routines, emphasizing its potential to streamline tasks, optimize time management, and provide valuable insights that can revolutionize individuals' work approaches. You'll then look more closely at ChatGPT's mechanics, its capabilities, limitations, and unique features. The book also outlines the best practices for utilizing ChatGPT, offering practical tips, techniques, and strategies to enhance output quality and reliability, while minimizing errors and maximizing results. You'll focus on ChatGPT's relevance in marketing tasks, such as generating product descriptions, creating email templates, automating social media posts, and addressing customer inquiries. The book concludes by exploring techniques for marketing with ChatGPT, including integration with other tools, data analysis, reporting, and customizing ChatGPT to meet specific marketing needs. In the end, you'll have the knowledge and skills needed to leverage ChatGPT's AI marketing capabilities and to harness its power for success in the digital age. What You'll Learn Understand the concepts and workings of ChatGPT, its architecture, and the training processApply the best practices for ChatGPTCreate email templates and automate social media posts using ChatGPTUse ChatGPT for data analysis and reporting Who This Book Is For Marketing professionals, business owners and entrepreneurs, content creators, and customer service representatives
R 1,140.00
Deep Swarm and Evolution for Generative Artificial Intelligence
This book provides theoretical and practical knowledge about swarm and evolutionary approach of generative AI and Large Language Models (LLMs). The development of such tools contributes to better optimizing methodologies with the integration of several machinelearning and deep learning techniques. In particular, it discusses how the “emergence” concept can contribute to the improvement of AI.The book aims to model human cognitive f unction in terms of “emergence” and to explain the feasibility of AI. To this end, it focuses on human perceptions of “utility.” It describes the emergence of various cognitive errors, and irrational behaviours in the multiobjective situations. It also reviews the cognitive differences and similarities between humans and LLMs. Such studies are important when applying LLMs to real-world tasks that involve human cognition, e.g., financial engineering and market issues.The book describes the intelligent behaviour of living organisms. This is to clarify how to achieve AI in the direction of artificial life. It describes sexual selection, which is a well-known natural phenomenon that troubled Darwin, i.e., why evolutionarily useless items evolved such as peacock feathers and moose antlers etc. The book shows how sexual selection is extended as “novelty search” for the application of generative AI, i.e., the image generation with diffusion model. Real-world applications are emphasised. Empirical examples from real-world data show how the concept of deep swarm and evolution is successfully applied when addressing tasks from such recent fields as robotics, e-commerce Web Shop and image generation etc.
R 2,711.00
R 305.00
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
Deep Swarm and Evolution for Generative Artificial Intelligence
This book provides theoretical and practical knowledge about swarm and evolutionary approach of generative AI and Large Language Models (LLMs). The development of such tools contributes to better optimizing methodologies with the integration of several machinelearning and deep learning techniques. In particular, it discusses how the “emergence” concept can contribute to the improvement of AI.The book aims to model human cognitive f unction in terms of “emergence” and to explain the feasibility of AI. To this end, it focuses on human perceptions of “utility.” It describes the emergence of various cognitive errors, and irrational behaviours in the multiobjective situations. It also reviews the cognitive differences and similarities between humans and LLMs. Such studies are important when applying LLMs to real-world tasks that involve human cognition, e.g., financial engineering and market issues.The book describes the intelligent behaviour of living organisms. This is to clarify how to achieve AI in the direction of artificial life. It describes sexual selection, which is a well-known natural phenomenon that troubled Darwin, i.e., why evolutionarily useless items evolved such as peacock feathers and moose antlers etc. The book shows how sexual selection is extended as “novelty search” for the application of generative AI, i.e., the image generation with diffusion model. Real-world applications are emphasised. Empirical examples from real-world data show how the concept of deep swarm and evolution is successfully applied when addressing tasks from such recent fields as robotics, e-commerce Web Shop and image generation etc.
R 8,143.64
Machine Learning and Artificial Intelligence in Marketing and Sales
Machine Learning and Artificial Intelligence in Marketing and Sales explores the ideas, and the statistical and mathematical concepts, behind Artificial Intelligence (AI) and machine learning models, as applied to marketing and sales, without getting lost in the details of mathematical derivations and computer programming.Bringing together the qualitative and the technological, and avoiding a simplistic broad overview, this book equips those in the field with methods to implement machine learning and AI models within their own organisations. Bridging the "Domain Specialist - Data Scientist Gap" (DS-DS Gap) is imperative to the success of this and chapters delve into this subject from a marketing practitioner and the data scientist perspective. Rather than a context-free introduction to AI and machine learning, data scientists implementing these methods for addressing marketing and sales problems will benefit most if they are exposed to how AI and machine learning have been applied specifically in the marketing and sales contexts.Marketing and sales practitioners who want to collaborate with data scientists can be much more effective when they expand their understanding across boundaries to include machine learning and AI.
R 4,546.93
Exploring Generative AI with Computational Intelligence
This book demystifies the concept of AI-driven creativity with an in-depth understanding of the underlying principles, algorithms, and applications of generative AI. It begins with a coverage of AI fundamentals, followed by a technical discussion including detailed explanations of model architectures, training processes, and optimisation techniques. It explores case studies showcasing how generative AI is reshaping industries such as entertainment, marketing, design, and healthcare. The book also tackles ethical considerations, addressing issues related to bias, transparency, and responsible AI development.Features:Provides deep understanding of generative AI, including in-depth coverage of various generative models such as GANs, VAEs, and RNNs.Includes practical, real-world examples of how generative AI is applied in different industries.Dedicates significant attention to ethical considerations.Equips readers with the knowledge and tools to build, train, and deploy their own generative AI systems.Offers thorough explanations of AI algorithms, neural network architectures, and training processes.This book is aimed at graduate students and researchers in computer engineering, AI and ML.
R 3,002.38
R 4,070.00
Authentic Marketing
Develop a marketing strategy that blends data-driven principles with authentic human insight to deliver stronger, more meaningful results.Authentic Marketing is a practical guide for mid-career marketers who want to build credibility, apply clear frameworks and develop campaigns that stand out in an increasingly AI-driven landscape. As conversations about automation dominate the industry, this book reframes what truly drives marketing effectiveness: human curiosity, creativity and audience-first thinking.Written by industry leader Visha Kudhail, the book provides actionable tools for integrating authentic inspiration with data-driven approaches. Through detailed chapters and real-world examples, it shows how to implement strategies that optimize performance, build trust and strengthen long-term consumer loyalty.You'll learn how to:- Apply audience-first principles to develop creative ideas grounded in real human insight- Implement data-driven strategies that support authenticity rather than replace it- Develop frameworks for balancing automation with the emotional intelligence marketing requires- Optimize campaigns by identifying meaningful audience motivations and behaviours- Use real-world examples to strengthen credibility and apply best practices across industriesWith its balance of strategy, practical guidance and modern industry insight, Authentic Marketing helps mid-career professionals develop campaigns that deliver measurable impact while staying true to the human foundations of great marketing.Themes include: marketing strategy, creativity frameworks, audience insight, authentic storytelling, data-driven marketing, campaign optimization
R 4,636.00
Contemporary Approaches of Digital Marketing and the Role of Machine Intelligence
Digital marketing emerged as a natural response by companies and vendors to leverage and benefit from the significant consumer concentration on digital channels. This proliferation of IT applications and the enormous presence of customers in digital channels generate a large number of products and customer data. Machine learning and artificial intelligence are game-changing techniques in digital marketing to analyze this data. This analysis helps marketers to personalize the sales tools toward individuals, optimize their operations, and minimize expenditure. Contemporary Approaches of Digital Marketing and the Role of Machine Intelligence demonstrates relevant theories of digital marketing along with tools, techniques, methods, and strategies. It also identifies the research gaps for effective digital marketing tools, techniques, and methods and builds a bridge between digital marketing strategies and business plans for organizations. Covering topics such as digital marketing, metaverse, and visitor experience, this premier reference source is an essential resource for business leaders and managers, marketers, IT managers, data analysts, social media analysts, students and educators of higher education, researchers, and academicians.
R 7,341.29
R 550.00
Machine Learning for Trading
Build and deploy AI-driven trading systems using the 7-Stage workflow with pandas, Polars, LightGBM, PyTorch, Optuna, zipline-reloaded, MLflow, Feast, and SHAPKey FeaturesBuild point-in-time pipelines, integrate alternative data, and ensure data integrityBuild and validate predictive models using GBMs, Transformers, and causal inference frameworks to create robust, interpretable alpha signalsDeploy RAG systems, autonomous financial agents, and diffusion-based synthetic data generatorsBook DescriptionThe rapid rise of AI and the growing complexity of financial markets have transformed quantitative trading into a data-driven, process-oriented discipline. This third edition provides a comprehensive blueprint for designing, validating, and deploying systematic trading strategies powered by modern machine learning. It introduces the 7 stage ML4T Workflow, a professional framework that unites data engineering, model development, validation, and live deployment into one cohesive process. It demonstrates how to turn raw market, fundamental, and alternative data into predictive signals and robust, production-ready trading systems. You’ll learn to build advanced pipelines for feature engineering, model evaluation, and portfolio optimization using libraries such as Polars, LightGBM, PyTorch, and Optuna. Practical notebooks illustrate every stage of the workflow, from factor testing and backtesting with zipline reloaded to live deployment with MLOps tools such as MLflow, Feast, and Prometheus. Additional coverage of synthetic data generation, Graph Neural Networks, and Reinforcement Learning extends the toolkit for building resilient, adaptive strategies that thrive in dynamic markets. By the end of this book, you’ll be proficient to build your own industrial-grade “alpha factory".What you will learnTransform raw data into predictive alpha factors, validated with leak-proof cross-validationMaster advanced models, from Gradient Boosting Machines to Transformers, Graph Neural Networks, and Reinforcement Learning agentsHarness Generative AI, Retrieval Augmented Generation, and Causal Inference to make models interpretable, auditable, and compliant with regulatory standardsBuild production-ready trading infrastructure using MLOps, feature stores, and model monitoring to transition research into live capital deployment safelyWho this book is forIf you are a data analyst, data scientist, Python developer, investment analyst, or portfolio manager interested in getting hands-on machine learning knowledge for trading, this book is for you. This book is for you if you want to learn how to extract value from a diverse set of data sources using machine learning to design your own systematic trading strategies. Some understanding of Python and machine learning techniques is required.
R 2,605.00
R 458.00
Generative AI and LLMs
Generative artificial intelligence (GAI) and large language models (LLM) are machine learning algorithms that operate in an unsupervised or semi-supervised manner. These algorithms leverage pre-existing content, such as text, photos, audio, video, and code, to generate novel content. The primary objective is to produce authentic and novel material. In addition, there exists an absence of constraints on the quantity of novel material that they are capable of generating. New material can be generated through the utilization of Application Programming Interfaces (APIs) or natural language interfaces, such as the ChatGPT developed by Open AI and Bard developed by Google. The field of generative artificial intelligence (AI) stands out due to its unique characteristic of undergoing development and maturation in a highly transparent manner, with its progress being observed by the public at large. The current era of artificial intelligence is being influenced by the imperative to effectively utilise its capabilities in order to enhance corporate operations. Specifically, the use of large language model (LLM) capabilities, which fall under the category of Generative AI, holds the potential to redefine the limits of innovation and productivity. However, as firms strive to include new technologies, there is a potential for compromising data privacy, long-term competitiveness, and environmental sustainability. This book delves into the exploration of generative artificial intelligence (GAI) and LLM. It examines the historical and evolutionary development of generative AI models, as well as the challenges and issues that have emerged from these models and LLM. This book also discusses the necessity of generative AI-based systems and explores the various training methods that have been developed for generative AI models, including LLM pretraining, LLM fine-tuning, and reinforcement learning from human feedback. Additionally, it explores the potential use cases, applications, and ethical considerations associated with these models. This book concludes by discussing future directions in generative AI and presenting various case studies that highlight the applications of generative AI and LLM.
R 5,955.00
Procedural Content Generation via Machine Learning
This second edition updates and expands upon the first beginner-focused guide to Procedural Content Generation via Machine Learning (PCGML), which is the use of computers to generate new types of content for video games (game levels, quests, characters, etc.) by learning from existing content. The authors survey current and future approaches to generating video game content and illustrate the major impact that PCGML has had on video games industry. In order to provide the most up-to-date information, this new edition incorporates the last two years of research and advancements in this rapidly developing area. The book guides readers on how best to set up a PCGML project and identify open problems appropriate for a research project or thesis. The authors discuss the practical and ethical considerations for PCGML projects and demonstrate how to avoid the common pitfalls. This second edition also introduces a new chapter on Generative AI, which covers the benefits, risks, and methods for applying pre-trained transformers to PCG problems.
R 1,649.00
AI-Powered B2B Marketing
How can mid-career B2B marketers effectively harness AI to build strategy and drive career impact?AI-Powered B2B Marketing offers clear, practical frameworks for professionals to implement AI technologies confidently and strategically. Backed by real-world examples and expert insights from global leaders including Epsilon, CACI UK and UrSpectr, this guide demystifies AI integration across B2B marketing. From powering market research to embedding ethical AI practices, it equips marketers to optimize every stage of the buyer journey while developing skills that elevate career credibility.You'll learn how to: - Develop strategic AI-driven frameworks tailored for B2B marketing- Implement actionable tools for lead generation, nurturing and account management- Apply principles of ethical AI use within marketing strategies- Optimize technology selection to align with business objectivesWritten by marketing innovator Simon Hall, this authoritative guide helps marketers transform B2B strategies, delivering measurable results and positioning you for career growth.Themes include: AI integration in B2B marketing, Strategic frameworks and models, Ethical AI application, Career development and impact, Real-world case studies
R 2,425.04
AI and Machine Learning Applications and Implications in Customer Support and Analytics
In the modern data-driven era, artificial intelligence (AI) and machine learning (ML) technologies that allow a computer to mimic intelligent human behavior are essential for organizations to achieve business excellence and assist organizations in extracting useful information from raw data. AI and ML have existed for decades, but in the age of big data, this sort of analysis is in higher demand than ever, especially for customer support and analytics. AI and Machine Learning Applications and Implications in Customer Support and Analytics investigates the applications of AI and ML and how they can be implemented to enhance customer support and analytics at various levels of organizations. This book is ideal for marketing professionals, managers, business owners, researchers, practitioners, academicians, instructors, university libraries, and students, and covers topics such as artificial intelligence, machine learning, supervised learning, deep learning, customer sentiment analysis, data mining, neural networks, and business analytics.
R 12,552.27
Contemporary Approaches of Digital Marketing and the Role of Machine Intelligence
Digital marketing emerged as a natural response by companies and vendors to leverage and benefit from the significant consumer concentration on digital channels. This proliferation of IT applications and the enormous presence of customers in digital channels generate a large number of products and customer data. Machine learning and artificial intelligence are game-changing techniques in digital marketing to analyze this data. This analysis helps marketers to personalize the sales tools toward individuals, optimize their operations, and minimize expenditure. Contemporary Approaches of Digital Marketing and the Role of Machine Intelligence demonstrates relevant theories of digital marketing along with tools, techniques, methods, and strategies. It also identifies the research gaps for effective digital marketing tools, techniques, and methods and builds a bridge between digital marketing strategies and business plans for organizations. Covering topics such as digital marketing, metaverse, and visitor experience, this premier reference source is an essential resource for business leaders and managers, marketers, IT managers, data analysts, social media analysts, students and educators of higher education, researchers, and academicians.
R 9,647.19
Modern Generative AI with ChatGPT and OpenAI Models
Harness the power of AI with innovative, real-world applications, and unprecedented productivity boosts, powered by the latest advancements in AI technology like ChatGPT and OpenAIPurchase of the print or Kindle book includes a free PDF eBookKey FeaturesExplore the theory behind generative AI models and the road to GPT3 and GPT4Become familiar with ChatGPT's applications to boost everyday productivityLearn to embed OpenAI models into applications using lightweight frameworks like LangChainBook DescriptionGenerative AI models and AI language models are becoming increasingly popular due to their unparalleled capabilities. This book will provide you with insights into the inner workings of the LLMs and guide you through creating your own language models. You'll start with an introduction to the field of generative AI, helping you understand how these models are trained to generate new data. Next, you'll explore use cases where ChatGPT can boost productivity and enhance creativity. You'll learn how to get the best from your ChatGPT interactions by improving your prompt design and leveraging zero, one, and few-shots learning capabilities. The use cases are divided into clusters of marketers, researchers, and developers, which will help you apply what you learn in this book to your own challenges faster. You'll also discover enterprise-level scenarios that leverage OpenAI models' APIs available on Azure infrastructure; both generative models like GPT-3 and embedding models like Ada. For each scenario, you'll find an end-to-end implementation with Python, using Streamlit as the frontend and the LangChain SDK to facilitate models' integration into your applications. By the end of this book, you'll be well equipped to use the generative AI field and start using ChatGPT and OpenAI models' APIs in your own projects.What you will learnUnderstand generative AI concepts from basic to intermediate levelFocus on the GPT architecture for generative AI modelsMaximize ChatGPT's value with an effective prompt designExplore applications and use cases of ChatGPTUse OpenAI models and features via API callsBuild and deploy generative AI systems with PythonLeverage Azure infrastructure for enterprise-level use casesEnsure responsible AI and ethics in generative AI systemsWho this book is forThis book is for individuals interested in boosting their daily productivity; businesspersons looking to dive deeper into real-world applications to empower their organizations; data scientists and developers trying to identify ways to boost ML models and code; marketers and researchers seeking to leverage use cases in their domain – all by using Chat GPT and OpenAI Models.A basic understanding of Python is required; however, the book provides theoretical descriptions alongside sections with code so that the reader can learn the concrete use case application without running the scripts.
R 1,693.00
