Data mining

Explore the differences between ICOs, cryptocurrencies, and tokens (offerings), enabling the reader to understand the ICO landscape, how millions were raised in minutes, and where the future of the tokenized economy is heading.

Speed up the design and implementation of deep learning solutions using Apache SparkKey FeaturesExplore the world of distributed deep learning with Apache SparkTrain neural networks with deep learning libraries such as BigDL and TensorFlowDevelop Spark deep learning applications to intelligently handle large and complex datasetsBook DescriptionDeep learning is a subset of machine learning where datasets with several layers of complexity can be processed.

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

Leverage the power of Hyperledger Fabric to develop Blockchain-based distributed ledgers with ease Key FeaturesWrite your own chaincode/smart contracts using Golang on hyperledger networkBuild and deploy decentralized applications (DApps)Dive into real world blockchain challenges such as integration and scalabilityBook DescriptionBBlockchain and Hyperledger technologiesare hot topics today.

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.

Learn what the Blockchain is, what the differences between available blockchain platforms are, how to work with Oracle's Blockchain Cloud Service, and how Blockchain can change the direction of your Oracle work and the focus of your customers.

Solve all big data problems by learning how to create efficient data modelsKey FeaturesCreate effective models that get the most out of big dataApply your knowledge to datasets from Twitter and weather data to learn big dataTackle different data modeling challenges with expert techniques presented in this bookBook DescriptionModeling and managing data is a central focus of all big data projects.

Learn what the Blockchain is, what the differences between available blockchain platforms are, how to work with Oracle's Blockchain Cloud Service, and how Blockchain can change the direction of your Oracle work and the focus of your customers.

Leverage Elastic Stack's machine learning features to gain valuable insight from your dataKey FeaturesCombine machine learning with the analytic capabilities of Elastic StackAnalyze large volumes of search data and gain actionable insight from themUse external analytical tools with your Elastic Stack to improve its performanceBook DescriptionMachine Learning with the Elastic Stack is a comprehensive overview of the embedded commercial features of anomaly detection and forecasting.

This book presents a comprehensive range of topics in deep learning for polymer discovery, from fundamental concepts to advanced methodologies.

Use the power of pandas to solve most complex scientific computing problems with ease.

Data and algorithms are changing our life.

Exploit the power of data in your business by building advanced predictive modeling applications with PythonAbout This BookMaster open source Python tools to build sophisticated predictive modelsLearn to identify the right machine learning algorithm for your problem with this forward-thinking guideGrasp the major methods of predictive modeling and move beyond the basics to a deeper level of understandingWho This Book Is ForThis book is designed for business analysts, BI analysts, data scientists, or junior level data analysts who are ready to move from a conceptual understanding of advanced analytics to an expert in designing and building advanced analytics solutions using Python.

A handy reference guide for data analysts and data scientists to help to obtain value from big data analytics using Spark on Hadoop clustersAbout This BookThis book is based on the latest 2.

Analyze your data and delve deep into the world of machine learning with the latest Spark version, 2.

Explore the web and make smarter predictions using PythonAbout This BookTargets two big and prominent markets where sophisticated web apps are of need and importance.

Make sense of your data and predict the unpredictableAbout This BookA unique book that centers around develop six key practical skills needed to develop and implement predictive analyticsApply the principles and techniques of predictive analytics to effectively interpret big dataSolve real-world analytical problems with the help of practical case studies and real-world scenarios taken from the world of healthcare, marketing, and other business domainsWho This Book Is ForThis book is for those with a mathematical/statistics background who wish to understand the concepts, techniques, and implementation of predictive analytics to resolve complex analytical issues.

Acquire and analyze data from all corners of the social web with PythonAbout This BookMake sense of highly unstructured social media data with the help of the insightful use cases provided in this guideUse this easy-to-follow, step-by-step guide to apply analytics to complicated and messy social dataThis is your one-stop solution to fetching, storing, analyzing, and visualizing social media dataWho This Book Is ForThis book is for intermediate Python developers who want to engage with the use of public APIs to collect data from social media platforms and perform statistical analysis in order to produce useful insights from data.

Group method of data handling (GMDH) is a typical inductive modeling method built on the principles of self-organization.

Master text-taming techniques and build effective text-processing applications with RAbout This BookDevelop all the relevant skills for building text-mining apps with R with this easy-to-follow guideGain in-depth understanding of the text mining process with lucid implementation in the R languageExample-rich guide that lets you gain high-quality information from text dataWho This Book Is ForIf you are an R programmer, analyst, or data scientist who wants to gain experience in performing text data mining and analytics with R, then this book is for you.

Simplify machine learning model implementations with SparkAbout This BookSolve the day-to-day problems of data science with SparkThis unique cookbook consists of exciting and intuitive numerical recipesOptimize your work by acquiring, cleaning, analyzing, predicting, and visualizing your dataWho This Book Is ForThis book is for Scala developers with a fairly good exposure to and understanding of machine learning techniques, but lack practical implementations with Spark.

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

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

The surging predictive analytics market is expected to grow from $10.

Predictive analytics is an evolving field and has applications across all domains and sectors.

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Departing from traditional methodologies of teaching data analysis, this book presents a dual-track learning experience, with both Executive and Technical Tracks, designed to accommodate readers with various learning goals or skill levels.

Artificial Intelligence and Knowledge Processing play a vital role in various automation industries and their functioning in converting traditional industries to AI-based factories.

This book is an accessible introduction to the study of detecting fake news on social media.

Unstructured text, as one of the most important data forms, plays a crucial role in data-driven decision making in domains ranging from social networking and information retrieval to scientific research and healthcare informatics.

Data profiling refers to the activity of collecting data about data, i.

This book presents pattern-based problem-solving methods for a variety of machine learning and data analysis problems.

Argumentation mining is an application of natural language processing (NLP) that emerged a few years ago and has recently enjoyed considerable popularity, as demonstrated by a series of international workshops and by a rising number of publications at the major conferences and journals of the field.

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

This book is written to address the issues relating to data gathering, data warehousing, and data analysis, all of which are useful when working with large amounts of data.

Public health thrives on high-quality evidence, yet acquiring meaningful data on a population remains a central challenge of public health research and practice.

Large-scale, highly interconnected networks, which are often modeled as graphs, pervade both our society and the natural world around us.

Graphs naturally represent information ranging from links between web pages, to communication in email networks, to connections between neurons in our brains.

This book introduces a novel perspective on machine learning, offering distinct advantages over neural network-based techniques.

Design for large-scale, high-performance queries using Snowflake's query processing engine to empower data consumers with timely, comprehensive, and secure access to data.

This text covers all of the data science, machine learning, and deep learning topics relevant to materials science and engineering, accompanied by numerous examples and applications.

Federated Learning: Unlocking the Power of Collaborative Intelligence is a definitive guide to the transformative potential of federated learning.

Graph Databases in Action introduces you to graph database concepts by comparing them with relational database constructs.

In today's fast-paced digital landscape, organizations face an ever-increasing volume of data that holds immense potential for driving business success.

Given a set of objects and a pairwise similarity measure between them, the goal of correlation clustering is to partition the objects in a set of clusters to maximize the similarity of the objects within the same cluster and minimize the similarity of the objects in different clusters.

Unstructured data is the most voluminous form of data in the world, and several elements are critical for any advanced analytics practitioner leveraging SAS software to effectively address the challenge of deriving value from that data.

Unstructured data is the most voluminous form of data in the world, and several elements are critical for any advanced analytics practitioner leveraging SAS software to effectively address the challenge of deriving value from that data.

See how data science can answer the questions your business faces!