ARTIFICIAL INTELLIGENCE & MACHINE LEARNING SERIES (8 results)

PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000.

PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000.

Condition: New. Print on Demand.

Condition: New. Print on Demand.

Taschenbuch. Condition: Neu. Neuware - Master the complete lifecycle of Machine Learning operations with practical MLOps techniques and modern AI deployment strategies.MLOps is a comprehensive guide designed for students, developers, researchers, and AI enthusiasts who want to understand how machine learning models are developed, deployed, monitored, and maintained in real-world environments.This book explains the integration of Machine Learning, DevOps, and Data Engineering practices to build scalable, reliable, and production-ready AI systems. Readers will explore the complete MLOps pipeline, from data preparation and model training to deployment, automation, monitoring, and continuous improvement.Inside This Book: Perfect For: This book provides a practical and industry-oriented approach to understanding MLOps, helping readers build modern, scalable, and efficient machine learning solutions for real-world applications.

Taschenbuch. Condition: Neu. Neuware - Unlock the power of data with this beginner-friendly guide to Data Science. Introduction to Data Science is designed for students, beginners, researchers, and aspiring professionals who want to understand how data is collected, analyzed, visualized, and transformed into meaningful insights.This book provides a clear introduction to the fundamental concepts, techniques, tools, and applications of Data Science using simple explanations and practical examples. Readers will learn about data analysis, statistics, data preprocessing, visualization, machine learning basics, and modern data-driven decision-making approaches used across industries.Inside this book, readers will explore: - Fundamentals of Data Science- Data Collection and Data Preparation- Exploratory Data Analysis (EDA)- Statistical Concepts for Data Science- Data Visualization Techniques- Introduction to Machine Learning- Python for Data Science- Big Data and Real-World Applications- Data Ethics and Decision Making- Industry Use Cases and Practical ExamplesWhether you are preparing for academics, projects, interviews, research, or a career in technology, this book serves as an essential starting point for learning modern Data Science concepts and workflows.Perfect for: - Engineering and degree students- Beginners entering Data Science and AI- Researchers and educators- Developers and technology enthusiasts- Self-learners and certification aspirantsBuild a strong foundation in Data Science and begin your journey into the world of intelligent data-driven technologies.

Paperback. Condition: new. Paperback. Master the complete lifecycle of Machine Learning operations with practical MLOps techniques and modern AI deployment strategies.MLOps is a comprehensive guide designed for students, developers, researchers, and AI enthusiasts who want to understand how machine learning models are developed, deployed, monitored, and maintained in real-world environments.This book explains the integration of Machine Learning, DevOps, and Data Engineering practices to build scalable, reliable, and production-ready AI systems. Readers will explore the complete MLOps pipeline, from data preparation and model training to deployment, automation, monitoring, and continuous improvement.Inside This Book: Perfect For: This book provides a practical and industry-oriented approach to understanding MLOps, helping readers build modern, scalable, and efficient machine learning solutions for real-world applications. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Paperback. Condition: new. Paperback. Unlock the power of data with this beginner-friendly guide to Data Science. Introduction to Data Science is designed for students, beginners, researchers, and aspiring professionals who want to understand how data is collected, analyzed, visualized, and transformed into meaningful insights.This book provides a clear introduction to the fundamental concepts, techniques, tools, and applications of Data Science using simple explanations and practical examples. Readers will learn about data analysis, statistics, data preprocessing, visualization, machine learning basics, and modern data-driven decision-making approaches used across industries.Inside this book, readers will explore: Fundamentals of Data ScienceData Collection and Data PreparationExploratory Data Analysis (EDA)Statistical Concepts for Data ScienceData Visualization TechniquesIntroduction to Machine LearningPython for Data ScienceBig Data and Real-World ApplicationsData Ethics and Decision MakingIndustry Use Cases and Practical ExamplesWhether you are preparing for academics, projects, interviews, research, or a career in technology, this book serves as an essential starting point for learning modern Data Science concepts and workflows.Perfect for: Engineering and degree studentsBeginners entering Data Science and AIResearchers and educatorsDevelopers and technology enthusiastsSelf-learners and certification aspirantsBuild a strong foundation in Data Science and begin your journey into the world of intelligent data-driven technologies. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.