Data capture and analysis

Master expert techniques for building automated and highly scalable end-to-end machine learning models and pipelines in Azure using TensorFlow, Spark, and KubernetesKey FeaturesMake sense of data on the cloud by implementing advanced analyticsTrain and optimize advanced deep learning models efficiently on Spark using Azure DatabricksDeploy machine learning models for batch and real-time scoring with Azure Kubernetes Service (AKS)Book DescriptionThe increase being seen in data volume today requires distributed systems, powerful algorithms, and scalable cloud infrastructure to compute insights and train and deploy machine learning (ML) models.

Information and how we manage, process and govern it is becoming increasingly important as organizations ride the wave of the big data revolution.

Data can be a cost for some organizations, but for those who succeed, it is a way to drive profitability, customer loyalty, and outperform others in their field.

Explore the entire Hyperledger blockchain family, including frameworks such as Fabric, Sawtooth, Indy, Burrow, and Iroha; and tools such as Composer, Explorer, and Caliper.

A beginner's guide to storing, managing, and analyzing data with the updated features of Elastic 7.

Implement real-world decentralized applications using Python, Vyper, Populus, and EthereumKey FeaturesStay up-to-date with everything you need to know about the blockchain ecosystemImplement smart contracts, wallets, and decentralized applications(DApps) using Python librariesGet deeper insights into storing content in a distributed storage platformBook DescriptionBlockchain is seen as the main technological solution that works as a public ledger for all cryptocurrency transactions.

Cyber Security for CEOs and Managment is a concise overview of the security threats posed to organizations and networks by the ubiquity of USB Flash Drives used as storage devices.

Perform advanced data manipulation tasks using pandas and become an expert data analyst.

With an emphasis on social science applications, Event History Analysis with R presents an introduction to survival and event history analysis using real-life examples.

This is the first comprehensive overview of the exciting field of the ''science of science''.

Do your product dashboards look funky?

This book explains the word association thematic analysis method, with examples, and gives practical advice for using it.

A student''s guide to setting up and conducting environmental research projects, including how to analyze data and write research proposals.

Leverage the power of Python and statistical modeling techniques for building accurate predictive modelsKey FeaturesGet introduced to Python's rich suite of libraries for statistical modelingImplement regression, clustering and train neural networks from scratchIncludes real-world examples on training end-to-end machine learning systems in PythonBook DescriptionPython's ease of use and multi-purpose nature has led it to become the choice of tool for many data scientists and machine learning developers today.

Modeling and Analysis of Compositional Data presents a practical and comprehensive introduction to the analysis of compositional data along with numerous examples to illustrate both theory and application of each method.

First place winner in Educational Products at the 2021 International Cartographic Conference Maps are ubiquitous, yet maps are not made equally, nor are they read equally.

Explore effective trading strategies in real-world markets using NumPy, spaCy, pandas, scikit-learn, and KerasKey FeaturesImplement machine learning algorithms to build, train, and validate algorithmic modelsCreate your own algorithmic design process to apply probabilistic machine learning approaches to trading decisionsDevelop neural networks for algorithmic trading to perform time series forecasting and smart analyticsBook DescriptionThe explosive growth of digital data has boosted the demand for expertise in trading strategies that use machine learning (ML).

Doing data science is difficult.

If you haven't modernized your data cleaning and reporting processes in Microsoft Excel, you're missing out on big productivity gains.

Data-driven insights are a key competitive advantage for any industry today, but deriving insights from raw data can still take days or weeks.

Get going with tidymodels, a collection of R packages for modeling and machine learning.

This book traces the techniques that have enabled the development of data-driven personas and how they can be leveraged as tools for empathizing and understanding users.

Data science unifies statistics, data analysis and machine learning to achieve a better understanding of the masses of data which are produced today, and to improve prediction.

Learn Azure's cloud capabilities with the help of this introductory guide to employing Azure for your cloud infrastructure needs.

This concise course in data analysis and inference for the mathematically literate builds on survey sampling and designed experiments.

Data Mining: Concepts and Techniques, Fourth Edition introduces concepts, principles, and methods for mining patterns, knowledge, and models from various kinds of data for diverse applications.

Get to grips with Kibana and its advanced functions to create interactive visualizations and dashboardsKey FeaturesExplore visualizations and perform histograms, stats, and map analyticsUnleash X-Pack and Timelion, and learn alerting, monitoring, and reporting featuresManage dashboards with Beats and create machine learning jobs for faster analyticsBook DescriptionKibana is one of the popular tools among data enthusiasts for slicing and dicing large datasets and uncovering Business Intelligence (BI) with the help of its rich and powerful visualizations.

Discover how to use Neo4j to identify relationships within complex and large graph datasets using graph modeling, graph algorithms, and machine learningKey FeaturesGet up and running with graph analytics with the help of real-world examplesExplore various use cases such as fraud detection, graph-based search, and recommendation systemsGet to grips with the Graph Data Science library with the help of examples, and use Neo4j in the cloud for effective application scalingBook DescriptionNeo4j is a graph database that includes plugins to run complex graph algorithms.

This book provides a comprehensive and accessible introduction to knowledge graphs, which have recently garnered notable attention from both industry and academia.

Get the most out of Elasticsearch 7's new features to build, deploy, and manage efficient applicationsKey FeaturesDiscover the new features introduced in Elasticsearch 7Explore techniques for distributed search, indexing, and clusteringGain hands-on knowledge of implementing Elasticsearch for your enterpriseBook DescriptionElasticsearch is one of the most popular tools for distributed search and analytics.

Gain hands-on experience of Python programming with industry-standard machine learning techniques using pandas, scikit-learn, and XGBoostKey FeaturesThink critically about data and use it to form and test a hypothesisChoose an appropriate machine learning model and train it on your dataCommunicate data-driven insights with confidence and clarityBook DescriptionIf data is the new oil, then machine learning is the drill.

Get the definitive handbook for manipulating, processing, cleaning, and crunching datasets in Python.

This approachable introduction to doing data science in R provides step-by-step advice on using the tools and statistical methods to carry out data analysis.

Learn how some Go-specific language features help to simplify building web scrapers along with common pitfalls and best practices regarding web scraping.

'Fascinating' - Financial TimesAlgorithms are running our society, and as the Cambridge Analytica story has revealed, we don't really know what they are up to.

Explore the entire Hyperledger blockchain family, including frameworks such as Fabric, Sawtooth, Indy, Burrow, and Iroha; and tools such as Composer, Explorer, and Caliper.

Knowing everything you can about each click to your Web site can help you make strategic decisions regarding your business.

This volume deals with two complementary topics.

This concise, easy-to-use reference puts one of the most popular frameworks for deep learning research and development at your fingertips.

Perform fast interactive analytics against different data sources using the Trino high-performance distributed SQL query engine.

Keyword Spotting (KWS) has been proposed as a flexible and more error-tolerant alternative to full transcriptions.