“…Along the way, you’ll find practical guidance for developing analytic thinking, operationalizing Big Data in global environments, and preparing for future analytical innovations. …”

“…This paper addresses the needs of technical professionals (consultants, technical support staff, IT Architects, and IT Specialists) who must deliver cost-effective cloud services and big data solutions…”

“…Provides insights into the latest research trends in hybrid intelligent algorithms and architectures Focuses on the application of hybrid intelligent techniques for pattern mining and recognition, in big data analytics, and in human-computer interaction Features hybrid intelligent applications in biomedical engineering and healthcare informatics…”

“…It really brings this home through the use of carefully chosen case studies that bring the overwhelming concept of 'big data' down to the personal level of individual life and health.” …”

“…Additionally, you'll explore the power of big data as a Service terminology implemented in OpenStack by integrating the Sahara project. …”

“…apply your knowledge by following featured practical projects covering everything from financial modeling to social media analysis Who This Book Is For Aimed for intermediate-to-advanced people (especially data scientist) who are already into the field of data science What You Will Learn Get to grips with R techniques to clean and prepare your data for analysis, and visualize your results Implement R machine learning algorithms from scratch and be amazed to see the algorithms in action Solve interesting real-world problems using machine learning and R as the journey unfolds Write reusable code and build complete machine learning systems from the ground up Learn specialized machine learning techniques for text mining, social network data, big data, and more Discover the different types of machine learning models and learn which is best to meet your data needs and solve your analysis problems Evaluate and improve the performance of machine learning models Learn specialized machine learning techniques for text mining, social network data, big data, and more In Detail R is the established language of data analysts and statisticians around the world. …”

“…Data scientists have to manage and maintain increasingly complex data projects, and with the rise of big data comes an increasing demand for computational and algorithmic efficiency. …”

“…Kirk address these parallels, their big data applications, and some anticipated analytics solutions, including Decision Science-as-a-Service. …”

“…Small data brings a completely different set of problems than big data. Instead of dealing with scale and efficiency, the game here is to draw statistical significant results from very few noisy examples. …”

“…About The Author Lazy Programmer: The Lazy Programmer is an AI and machine learning engineer with a focus on deep learning, who also has experience in data science, big data engineering, and full-stack software engineering. …”

“…About The Author Lazy Programmer: The Lazy Programmer is an AI and machine learning engineer with a focus on deep learning, who also has experience in data science, big data engineering, and full-stack software engineering. …”

“…What you will learn Understand the role of distributed computing in the world of big data Gain an appreciation for Apache Spark as the de facto go-to for big data processing Scale out your data analytics process using Apache Spark Build data pipelines using data lakes, and perform data visualization with PySpark and Spark SQL Leverage the cloud to build truly scalable and real-time data analytics applications Explore the applications of data science and scalable machine learning with PySpark Integrate your clean and curated data with BI and SQL analysis tools Who this book is for This book is for practicing data engineers, data scientists, data analysts, and data enthusiasts wh ..…”

“…This book will serve as a comprehensive guide to mastering BigQuery, and how you can utilize it to quickly and efficiently get useful insights from your Big Data. You will begin with getting a quick overview of the Google Cloud Platform and the various services it supports. …”

“…Later chapters will get you up to speed with connecting and retrieving data from SQL Server 2019 Big Data Clusters, and even show you how to extend and customize the SSIS toolbox using custom-developed tasks and transforms. …”

“…Slow code will kill a big data project. Fast pure-Python code, optimized libraries, and fully utilized multiprocessor hardware are the price of entry for machine learning and large-scale data analysis. …”

“…In addition, the book explores the blockchain and its with other technologies like Internet of Things, big data and artificial intelligence, etc."--…”

“….- Shows you how users interact with the system in natural language- Explains how cognitive analysis/AI can source "big data"- Provides a roadmap for implementation- Gets you up to speed now before you get left behind…”

“…Due to COVID-19, the conference was held virtually on August 13–15, 2021, jointly held by the School of Mathematics of Renmin University of China, the Engineering Research Center of Financial Computing and Digital Engineering of Ministry of Education, the Statistics and Big Data Research Institute of Renmin University of China, the Blockchain Research Institute of Renmin University of China, the Zhongguancun Internet Finance Research Institute, and the Renmin University Press…”

“…In the end, readers will learn some of the latest technological advancements in building a scalable machine learning model with Big Data…”

“…Particular topics of interest include (but are not limited to): Applied ecology and the management of biological resources (including wildlife and habitat management, land use and management, aquatic resources, restoration ecology); Theoretical ecology and modelling; Biodiversity and species abundance; Conservation (including planning and risk assessment); Animal ecology; Microbial ecology; Evolution ecology; Chemical and molecular ecology; Marine ecology; Behavioural ecology; Remote sensing and ecology; Ecosystems and biospheres as complex adaptive systems; Tools and computational methods to study ecological systems (including AI, informatics and Big Data); Ecology and society…”