Идеальный компаньон для повышения ваших навыков и применения техник хранения, обработки и анализа данных для обоснованных бизнес-решений. Выберите лучший из инструментов, таких как платформы Hadoop, R, Python, Spark, NoSQL для массового онлайн-анализа. Следуйте по стопам экспертов, чтобы узнать статистический вывод, машинное обучение, математическое моделирование и визуализацию данных.
A perfect companion to boost your skills and apply techniques to store, process and analyse data for informed business decisions. Choose the best of the tools such as Hadoop, R, Python, Spark, NoSQL platforms to do Massive online Analysis. Follow an experts footsteps to learn statistical inference, machine learning, mathematical modelling and data visualisation.
Book Description Big Data Analytics relates to the strategies used by organizations to collect, organize and analyze large amounts of data to bring out hidden patterns and insights from the data which otherwise cannot be analyzed through traditional systems.
Through this book, you'll learn to setup big data environment on the AWS/Azure platform and configure various tools for performing analytical operations on big data table comprising of millions of records. Furthermore, you'll learn to explore various other components of hadoop ecosystem such as YARN, MapReduce, HDFS, HIVE, etc to perform various analytical operations. As you progress further, you'll be introduced to NoSQL databases for efficient querying and storage of data. To scale up processing time you'll learn to integrate Spark in to your environment and understand how its components - Spark Streaming, MLLib, etc can be used for quicker computations.
Once you have gained mastery over mining and organizing the data, you'll learn to derive ad interpret meaningful analysis of data using predictive, prescriptive, statistical and other form of machine learning techniques. You'll learn to implement various supervised, unsupervised and deep learning models with the help of real-world examples to gain detailed sense of understanding of machine learning is in practice. By the end of the book, you will have a very clear and concrete understanding of what Big Data Analytics means, what tools and techniques organizations are using to implement their Big Data platforms, how they are driving revenues and how users can develop their own solution based on the step-by-step approach articulated in the book.
What you will learn Understand the (Real) meaning of Big Data Analytics and how it can help you in transforming your organization Provide a concrete framework of formulating a custom winning Big Data strategy for the enterprise Discuss industry-wide trends from real-world deployments of Big Data platforms across the industry Discuss how C-Level management in large global organisations are approaching their Big Data strategy Provide hands-on examples in various sections for more seasoned software professionals Simple lucid explanations to demystify confusing terms commonly used in Big Data Analytics & Data Science Provide step-by-step explanation of various Big Data topics in a chronological order but each chapter can also be read independently due to the modular organization of the chapters Develop, lead and put together a cost-effective yet robust enterprise-wide Analytics platform Going beyond general-purpose analytics to develop high-performance cutting edge analytic capabilities
The first textbook to teach students how to build data analytic solutions on large data sets using cloud-based technologies. This is the first textbook to teach students how to build data analytic solutions on large data sets (specifically in Internet of Things applications) using cloud-based technologies for data storage, transmission and mashup, ...
Learn the basics of Data Science through an easy to understand conceptual framework and immediately practice using RapidMiner platform. Whether you are brand new to data science or working on your tenth project, this book will show you how to analyze data, uncover hidden patterns and relationships to aid important decisions and predictions.
Social Media and the Internet of Things have resulted in an avalanche of data. Data is powerful but not in its raw form; it needs to be processed and modeled, and Python is one of the most robust tools out there to do so. It has an array of packages for predictive modeling and a suite of IDEs to choose from. Using the Python programming language, a ...
Powerful smart applications using deep learning algorithms to dominate numerical computing, deep learning, and functional programming. Machine learning has had a huge impact on academia and industry by turning data into actionable information. Scala has seen a steady rise in adoption over the past few years, especially in the fields of data science ...
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