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Advanced Applications of Machine Learning in Big Data Analytics
Nowadays, data is seen as a valuable asset in the digital world, helping to drive innovation and change various businesses. A new paradigm in data analysis and understanding has emerged as a result of the explosion of linked devices, social media, and scientific progress, which has led to an exponential expansion in data. Massive, rapidly changing, and diverse data sets constitute big data, which brings with it new possibilities and formidable obstacles. Using sophisticated machine learning methods is now crucial for deriving useful conclusions from such a large dataset.
"Advanced Applications of Machine Learning in Big Data Analytics" is an attempt to give a thorough examination of the state-of-the-art approaches and practical uses that are transforming data-driven decision-making. From healthcare and banking to marketing and natural language processing, we explore the theoretical underpinnings of machine learning and highlight its practical applications across several domains.
Everyone from data scientists and analysts to researchers and corporate executives as well as students will find something of interest in this book. This book provides helpful information and advice for anyone who wants to learn more about machine learning, its practical applications, or the bigger picture of big data analytics, or who wants to improve their technical abilities.
Deep learning, generative models, and reinforcement learning are just a few of the sophisticated machine learning techniques that we will be covering in detail throughout the chapters. These strategies allow us to take on difficult challenges that were previously insurmountable using conventional data analysis approaches. Data privacy, prejudice, and explainability are just a few of the ethical concerns and problems with big data analytics that we will go over.
The goal of this book is to teach readers how to use machine learning and big data analytics by covering the fundamentals, as well as presenting examples and real-world case studies. We are certain that these cutting-edge methods, if mastered, will allow us to realise data's full potential and propel innovation in a wide range of sectors.
"Advanced Applications of Machine Learning in Big Data Analytics" is an attempt to give a thorough examination of the state-of-the-art approaches and practical uses that are transforming data-driven decision-making. From healthcare and banking to marketing and natural language processing, we explore the theoretical underpinnings of machine learning and highlight its practical applications across several domains.
Everyone from data scientists and analysts to researchers and corporate executives as well as students will find something of interest in this book. This book provides helpful information and advice for anyone who wants to learn more about machine learning, its practical applications, or the bigger picture of big data analytics, or who wants to improve their technical abilities.
Deep learning, generative models, and reinforcement learning are just a few of the sophisticated machine learning techniques that we will be covering in detail throughout the chapters. These strategies allow us to take on difficult challenges that were previously insurmountable using conventional data analysis approaches. Data privacy, prejudice, and explainability are just a few of the ethical concerns and problems with big data analytics that we will go over.
The goal of this book is to teach readers how to use machine learning and big data analytics by covering the fundamentals, as well as presenting examples and real-world case studies. We are certain that these cutting-edge methods, if mastered, will allow us to realise data's full potential and propel innovation in a wide range of sectors.
278 pages, Kindle Edition
Published December 11, 2024
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