Data capture and analysis

A practical blockchain handbook designed to take you through implementing and re-engineering banking and financial solutions and workflows using eight step-by-step projectsKey FeaturesImplement various end-to-end blockchain projects and learn to enhance present-day financial solutionsUse Ethereum, Hyperledger, and Stellar to build public and private decentralized applicationsAddress complex challenges faced in the BFSI domain using different blockchain platform servicesBook DescriptionBlockchain technology will continue to play an integral role in the banking and finance sector in the coming years.

The real-world data, though massive, is largely unstructured, in the form of natural-language text.

Become the master player of data exploration by creating reproducible data processing pipelines, visualizations, and prediction models for your applications.

This book focuses on techniques for automating the procedure of creating external labelings, also known as callout labelings.

Object-Oriented Analysis and Design for Information Systems, Second Edition clearly explains real object-oriented programming in practice.

Get started with Ray, the open source distributed computing framework that simplifies the process of scaling compute-intensive Python workloads.

Master scala's advanced techniques to solve real-world problems in data analysis and gain valuable insights from your dataKey FeaturesA beginner's guide for performing data analysis loaded with numerous rich, practical examplesAccess to popular Scala libraries such as Breeze, Saddle for efficient data manipulation and exploratory analysisDevelop applications in Scala for real-time analysis and machine learning in Apache SparkBook DescriptionEfficient business decisions with an accurate sense of business data helps in delivering better performance across products and services.

Data is constantly increasing and data analysts are in higher demand than ever.

Learn to construct state-of-the-art simulation models with Python and enhance your simulation modelling skills, as well as create and analyze digital prototypes of physical models with easeKey FeaturesUnderstand various statistical and physical simulations to improve systems using PythonLearn to create the numerical prototype of a real model using hands-on examplesEvaluate performance and output results based on how the prototype would work in the real worldBook DescriptionSimulation modelling is an exploration method that aims to imitate physical systems in a virtual environment and retrieve useful statistical inferences from it.

Microprocessor Engineering provides an insight in the structures and operating techniques of a small computer.

Enter the exciting world of Julia, a high-performance language for technical computingKey FeaturesLeverage Julia's high speed and efficiency for your applicationsWork with Julia in a multi-core, distributed, and networked environmentApply Julia to tackle problems concurrently and in a distributed environmentBook DescriptionThe release of Julia 1.

Provides an important framework for data analysts in assessing the quality of data and its potential to provide meaningful insights through analysis Analytics and statistical analysis have become pervasive topics, mainly due to the growing availability of data and analytic tools.

Implementing Analytics demystifies the concept, technology and application of analytics and breaks its implementation down to repeatable and manageable steps, making it possible for widespread adoption across all functions of an organization.

Pattern Recognition on Oriented Matroids covers a range of innovative problems in combinatorics, poset and graph theories, optimization, and number theory that constitute a far-reaching extension of the arsenal of committee methods in pattern recognition.

Even as big data is turning the world upside down, the next phase of the revolution is already taking shape: real-time data analysis.

Take advantage of today's sky-high demand for data engineers.

Gain hands-on experience with industry-standard data analysis and machine learning tools in PythonKey FeaturesTackle data science problems by identifying the problem to be solvedIllustrate patterns in data using appropriate visualizationsImplement suitable machine learning algorithms to gain insights from dataBook DescriptionData Science Projects with Python is designed to give you practical guidance on industry-standard data analysis and machine learning tools, by applying them to realistic data problems.

Your hands-on reference guide to developing, training, and optimizing your machine learning modelsKey FeaturesYour guide to learning efficient machine learning processes from scratchExplore expert techniques and hacks for a variety of machine learning conceptsWrite effective code in R, Python, Scala, and Spark to solve all your machine learning problemsBook DescriptionMachine learning makes it possible to learn about the unknowns and gain hidden insights into your datasets by mastering many tools and techniques.

Measuring the abundance of individuals and the diversity of species are core components of most ecological research projects and conservation monitoring.

Learn to extract actionable insights from your big data in real time using a range of Microsoft Azure featuresKey FeaturesUpdated with the latest features and new additions to Microsoft AzureMaster the fundamentals of cloud analytics using AzureLearn to use Azure Synapse Analytics (formerly known as Azure SQL Data Warehouse) to derive real-time customer insightsBook DescriptionCloud Analytics with Microsoft Azure serves as a comprehensive guide for big data analysis and processing using a range of Microsoft Azure features.

Get a firm grip on the core processes including browser automation, web scraping, Word, Excel, and GUI automation with Python 3.

Medical data exists in several formats, from structured data and medical reports to 1D signals, 2D images, 3D volumes, or even higher dimensional data such as temporal 3D sequences.

Learn how to architect, implement, and administer a complex Splunk Enterprise environment and extract valuable insights from business data.

Modern Fortran teaches you to develop fast, efficient parallel applications using twenty-first-century Fortran.

Lead your demand planning process to excellence and deliver real value to your supply chain.

Get up and running with the fundamentals of Bitcoin and blockchainKey FeaturesLearn quick, effective, and easy ways to master blockchain and Bitcoin Understand the impact of decentralization and discover ways to tackle it Explore the future of Bitcoin and blockchain and implement them in a business networkBook DescriptionBlockchain is a distributed database that enables permanent, transparent, and secure storage of data.

Use PySpark to easily crush messy data at-scale and discover proven techniques to create testable, immutable, and easily parallelizable Spark jobsKey FeaturesWork with large amounts of agile data using distributed datasets and in-memory cachingSource data from all popular data hosting platforms, such as HDFS, Hive, JSON, and S3Employ the easy-to-use PySpark API to deploy big data Analytics for productionBook DescriptionApache Spark is an open source parallel-processing framework that has been around for quite some time now.

Most biologists use nonlinear regression more than any other statistical technique, but there are very few places to learn about curve-fitting.

How can you get your data from frontend servers to Hadoop in near real time?

Learn how to use, deploy, and maintain Apache Spark with this comprehensive guide, written by the creators of the open-source cluster-computing framework.

The mobile threat landscape is evolving bringing about new forms of data loss.

A practical guide to data mining using SQL and Excel Data Analysis Using SQL and Excel, 2nd Edition shows you how to leverage the two most popular tools for data query and analysis SQL and Excel to perform sophisticated data analysis without the need for complex and expensive data mining tools.

Teach your machine to think for itself!

Advances in Information Storage Systems (AISS) series was initiated by ASME Press.

Web Scraping techniques are getting more popular, since data is as valuable as oil in 21st century.

Effective visualization is the best way to communicate information from the increasingly large and complex datasets in the natural and social sciences.

Advances in Imaging and Electron Physics merges two long-running serials-Advances in Electronics and Electron Physics and Advances in Optical and Electron Microscopy.

Build, manage, and configure high-performing, reliable NoSQL database for your applications with CassandraKey FeaturesWrite programs more efficiently using Cassandra's features with the help of examplesConfigure Cassandra and fine-tune its parameters depending on your needsIntegrate Cassandra database with Apache Spark and build strong data analytics pipelineBook DescriptionWith ever-increasing rates of data creation, the demand for storing data fast and reliably becomes a need.

Food Science and Technology: A Series of Monographs: Food Texture and Viscosity: Concept and Measurement focuses on the texture and viscosity of food and how these properties are measured.

This book surveys the myriad facets of monitoring people in motion, from spatio-temporal data modeling, to data aggregation and warehousing, to data analysis.

BIG DATA, ARTIFICIAL INTELLIGENCE AND DATA ANALYSIS SET Coordinated by Jacques Janssen Data analysis is a scientific field that continues to grow enormously, most notably over the last few decades, following rapid growth within the tech industry, as well as the wide applicability of computational techniques alongside new advances in analytic tools.

Data is an increasingly important business asset and enabler for organisational activities.

Designed with beginners in mind, this workshop helps you make the most of Python libraries and the Jupyter Notebook's functionality to understand how data science can be applied to solve real-world data problems.

Mathematical Methods in Data Science covers a broad range of mathematical tools used in data science, including calculus, linear algebra, optimization, network analysis, probability and differential equations.

Harness the full power of the behavioral data in your company by learning tools specifically designed for behavioral data analysis.

Big Data: Principles and Paradigms captures the state-of-the-art research on the architectural aspects, technologies, and applications of Big Data.