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(as of Apr 25, 2024 22:13:40 UTC – Details)
Discover the use of graph networks to develop a new approach to data science using theoretical and practical methods with this expert guide using Python, printed in color
Key FeaturesCreate networks using data points and informationLearn to visualize and analyze networks to better understand communitiesExplore the use of network data in both – supervised and unsupervised machine learning projectsPurchase of the print or Kindle book includes a free PDF eBookBook Description
Network analysis is often taught with tiny or toy data sets, leaving you with a limited scope of learning and practical usage. Network Science with Python helps you extract relevant data, draw conclusions and build networks using industry-standard – practical data sets. You’ll begin by learning the basics of natural language processing, network science, and social network analysis, then move on to programmatically building and analyzing networks. You’ll get a hands-on understanding of the data source, data extraction, interaction with it, and drawing insights from it. This is a hands-on book with theory grounding, specific technical, and mathematical details for future reference. As you progress, you’ll learn to construct and clean networks, conduct network analysis, egocentric network analysis, community detection, and use network data with machine learning. You’ll also explore network analysis concepts, from basics to an advanced level.
By the end of the book, you’ll be able to identify network data and use it to extract unconventional insights to comprehend the complex world around you.
What you will learnExplore NLP, network science, and social network analysisApply the tech stack used for NLP, network science, and analysisExtract insights from NLP and network dataGenerate personalized NLP and network projectsAuthenticate and scrape tweets, connections, the web, and data streamsDiscover the use of network data in machine learning projectsWho this book is for
Network Science with Python demonstrates how programming and social science can be combined to find new insights. Data scientists, NLP engineers, software engineers, social scientists, and data science students will find this book useful. An intermediate level of Python programming is a prerequisite. Readers from both – social science and programming backgrounds will find a new perspective and add a feather to their hat.
Table of ContentsIntroducing Natural Language ProcessingNetwork AnalysisUseful Python LibrariesNLP and Network SynergyEven Easier ScrapingGraph Construction and CleaningWhole Network AnalysisEgocentric Network AnalysisCommunity DetectionSupervised Machine Learning on Network DataUnsupervised Machine Learning on Network Data
ASIN : B0BJKP7R4P
Publisher : Packt Publishing; 1st edition (February 28, 2023)
Publication date : February 28, 2023
Language : English
File size : 31252 KB
Text-to-Speech : Enabled
Screen Reader : Supported
Enhanced typesetting : Enabled
X-Ray : Not Enabled
Word Wise : Not Enabled
Sticky notes : On Kindle Scribe
Print length : 414 pages
