{"title":"Sunila Gollapudi","description":null,"products":[{"product_id":"getting-started-with-greenplum-for-big-data-analytics-book-sunila-gollapudi-9781782177043","title":"Getting Started with Greenplum for Big Data Analytics","description":"A hands-on guide on how to execute an analytics project from conceptualization to operationalization using Greenplum  Key Features  Explore the software components and appliance modules available in Greenplum Learn core Big Data architecture concepts and master data loading and processing patterns Understand Big Data problems and the data science lifecycle  Book DescriptionOrganizations are leveraging the use of data and analytics to gain a competitive advantage over their opposition. Therefore, organizations are quickly becoming more and more data driven. With the advent of Big Data, existing Data Warehousing and Business Intelligence solutions are becoming obsolete, and a requisite for new agile platforms consisting of all the aspects of Big Data has become inevitable. From loading\/integrating data to presenting analytical visualizations and reports, the new Big Data platforms like Greenplum do it all. It is now the mindset of the user that requires a tuning to put the solutions to work.  \"Getting Started with Greenplum for Big Data Analytics\" is a practical, hands-on guide to learning and implementing Big Data Analytics using the Greenplum Integrated Analytics Platform. From processing structured and unstructured data to presenting the results\/insights to key business stakeholders, this book explains it all.  \"Getting Started with Greenplum for Big Data Analytics\" discusses the key characteristics of Big Data and its impact on current Data Warehousing platforms. It will take you through the standard Data Science project lifecycle and will lay down the key requirements for an integrated analytics platform. It then explores the various software and appliance components of Greenplum and discusses the relevance of each component at every level in the Data Science lifecycle.  You will also learn Big Data architectural patterns and recap some key advanced analytics techniques in detail. The book will also take a look at programming with R and integration with Greenplum for implementing analytics. Additionally, you will explore MADlib and advanced SQL techniques in Greenplum for analytics. This book also elaborates on the physical architecture aspects of Greenplum with guidance on handling high-availability, back-up, and recovery.What you will learn  Load data from multiple data sources using the built-in ELT \/ ETL Learn Parallel Processing \/ MPP \/ MapReduce techniques Program with R and MADlib Understand back-up and recovery implementation in Greenplum Optimize data processing and querying using optimal distribution and partitioning strategies Exchange data between the Greenplum Database and Hadoop Handle high-availability requirements on Greenplum Integrate ETL, reporting, and visualization tools  Who this book is for\"Getting Started with Greenplum for Big Data\" Analytics is great for data scientists and data analysts with a basic knowledge of Data Warehousing and Business Intelligence platforms who are new to Big Data and who are looking to get a good grounding in how to use the Greenplum Platform. It's assumed that you will have some experience with database design and programming as well as be familiar with analytics tools like R and Weka.","brand":"WoB","offers":[{"title":"- \/ - \/ -","offer_id":51191308321041,"sku":"","price":0.0,"currency_code":"GBP","in_stock":true},{"title":"US \/ NEW \/ INGRAM","offer_id":51191310188817,"sku":"NIN9781782177043","price":0.0,"currency_code":"GBP","in_stock":false},{"title":"GB \/ NEW \/ INGRAM","offer_id":52425682583825,"sku":"NLS9781782177043","price":0.0,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0784\/4072\/6801\/files\/1782177043.jpg?v=1751345158"},{"product_id":"practical-machine-learning-book-sunila-gollapudi-9781784399689","title":"Practical Machine Learning","description":"Tackle the real-world complexities of modern machine learning with innovative, cutting-edge, techniques  About This Book  • Fully-coded working examples using a wide range of machine learning libraries and tools, including Python, R, Julia, and Spark • Comprehensive practical solutions taking you into the future of machine learning • Go a step further and integrate your machine learning projects with Hadoop  Who This Book Is For  This book has been created for data scientists who want to see machine learning in action and explore its real-world application. With guidance on everything from the fundamentals of machine learning and predictive analytics to the latest innovations set to lead the big data revolution into the future, this is an unmissable resource for anyone dedicated to tackling current big data challenges. Knowledge of programming (Python and R) and mathematics is advisable if you want to get started immediately.  What You Will Learn  • Implement a wide range of algorithms and techniques for tackling complex data • Get to grips with some of the most powerful languages in data science, including R, Python, and Julia • Harness the capabilities of Spark and Hadoop to manage and process data successfully • Apply the appropriate machine learning technique to address real-world problems • Get acquainted with Deep learning and find out how neural networks are being used at the cutting-edge of machine learning • Explore the future of machine learning and dive deeper into polyglot persistence, semantic data, and more  In Detail  Finding meaning in increasingly larger and more complex datasets is a growing demand of the modern world. Machine learning and predictive analytics have become the most important approaches to uncover data gold mines. Machine learning uses complex algorithms to make improved predictions of outcomes based on historical patterns and the behaviour of data sets. Machine learning can deliver dynamic insights into trends, patterns, and relationships within data, immensely valuable to business growth and development. This book explores an extensive range of machine learning techniques uncovering hidden tricks and tips for several types of data using practical and real-world examples. While machine learning can be highly theoretical, this book offers a refreshing hands-on approach without losing sight of the underlying principles. Inside, a full exploration of the various algorithms gives you high-quality guidance so you can begin to see just how effective machine learning is at tackling contemporary challenges of big data. This is the only book you need to implement a whole suite of open source tools, frameworks, and languages in machine learning. We will cover the leading data science languages, Python and R, and the underrated but powerful Julia, as well as a range of other big data platforms including Spark, Hadoop, and Mahout. Practical Machine Learning is an essential resource for the modern data scientists who want to get to grips with its real-world application. With this book, you will not only learn the fundamentals of machine learning but dive deep into the complexities of real world data before moving on to using Hadoop and its wider ecosystem of tools to process and manage your structured and unstructured data. You will explore different machine learning techniques for both supervised and unsupervised learning; from decision trees to Naive Bayes classifiers and linear and clustering methods, you will learn strategies for a truly advanced approach to the statistical analysis of data. The book also explores the cutting-edge advancements in machine learning, with worked examples and guidance on deep learning and reinforcement learning, providing you with practical demonstrations and samples that help take the theory–and mystery–out of even the most advanced machine learning methodologies.  Style and approach  A practical data science tutorial designed to give you an insight into the practical application of machine learning, this book takes you through complex concepts and tasks in an accessible way. Featuring information on a wide range of data science techniques, Practical Machine Learning is a comprehensive data science resource.","brand":"WoB","offers":[{"title":"- \/ - \/ -","offer_id":51234099331345,"sku":"","price":0.0,"currency_code":"GBP","in_stock":true},{"title":"US \/ NEW \/ INGRAM","offer_id":51234099986705,"sku":"NIN9781784399689","price":0.0,"currency_code":"GBP","in_stock":false},{"title":"GB \/ NEW \/ INGRAM","offer_id":52614719373585,"sku":"NLS9781784399689","price":0.0,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0784\/4072\/6801\/files\/178439968X.jpg?v=1750962762"},{"product_id":"learn-computer-vision-using-opencv-book-sunila-gollapudi-9781484242605","title":"Learn Computer Vision Using OpenCV","description":"Build practical applications of computer vision using the OpenCV library with Python. This book discusses different facets of computer vision such as image and object detection, tracking and motion analysis and their applications with examples.  The author starts with an introduction to computer vision followed by setting up OpenCV from scratch using Python. The next section discusses specialized image processing and segmentation and how images are stored and processed by a computer. This involves pattern recognition and image tagging using the OpenCV library. Next, you’ll work with object detection, video storage and interpretation, and human detection using OpenCV. Tracking and motion is also discussed in detail. The book also discusses creating complex deep learning models with CNN and RNN. The author finally concludes with recent applications and trends in computer vision. After reading this book, you will be able to understand and implement computer vision and its applications with OpenCV using Python. You will also be able to create deep learning models with CNN and RNN and understand how these cutting-edge deep learning architectures work. What You Will Learn  Understand what computer vision is, and its overall application in intelligent automation systems  Discover the deep learning techniques required to build computer vision applications  Build complex computer vision applications using the latest techniques in OpenCV, Python, and NumPy  Create practical applications and implementations such as face detection and recognition, handwriting recognition, object detection, and tracking and motion analysis    Who This Book Is ForThose who have a basic understanding of machine learning and Python and are looking to learn computer vision and its applications.","brand":"WoB","offers":[{"title":"GB \/ NEW \/ INGRAM","offer_id":52481825440017,"sku":"NLS9781484242605","price":0.0,"currency_code":"GBP","in_stock":true},{"title":"US \/ NEW \/ INGRAM","offer_id":52748966002961,"sku":"NIN9781484242605","price":0.0,"currency_code":"GBP","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0784\/4072\/6801\/files\/9781484242605.jpg?v=1759852295"}],"url":"https:\/\/www.worldofbooks.com\/en-gb\/collections\/author-books-by-sunila-gollapudi.oembed","provider":"World of Books ","version":"1.0","type":"link"}