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Python for Graph and Network Analysis

This research monograph provides the means to learn the theory and practice of graph and network analysis using the Python programming;

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Graph Analysis & Visualization

into the real world. Using sophisticated methods and tools that span analysis functions, this guide shows you how to exploit graph and network;

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Building Web Applications with Python and Neo4j

Python and Neo4j using Py2neo Develop REST-based services over social network data using Flask and object graph models over Neo4j Integrate;

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Mastering Python Networking

use Python for network automation, programmability, and data analysis. Basic familiarity with Python programming and networking-related;

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Creativity in Load-Balance Schemes for Multi/Many-Core Heterogeneous Graph Computing

-balance schemes for heterogeneous graph processing, and trends and challenges in large-scale HPC network analysis''--;

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Biological Network Analysis

Biological Network Analysis: Trends, Approaches, Graph Theory, and Algorithms considers three major biological networks, including Gene;

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Graph Representation Learning

, recommender systems, question answering, and social network analysis. This book provides a synthesis and overview of graph representation;

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Hybrid Graph Theory and Network Analysis

aspects of network analysis. This approach is called here hybrid graph theory. This is essentially a vertex-independent view of graphs naturally;

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Network Security Through Data Analysis

analysis and visualization Detect unusual phenomena through Exploratory Data Analysis (EDA) Identify significant structures in networks with graph;

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Learn PySpark

-time predictions. This book concludes with a discussion on graph frames and performing network analysis using graph algorithms in PySpark. All;

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Learn PySpark

models for real-time predictions. This book concludes with a discussion on graph frames and performing network analysis using graph algorithms;

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Python Network Programming

the chapters, you'll use Python for DevOps and open source tools to test, secure, and analyze your network. Toward the end, you'll develop;

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Graph-Based Representations in Pattern Recognition

analysis, and graph theory. They cover topics such as graph edit distance, graph matching, machine learning for graph problems, network and graph;

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Graph Theory

structuring the contents of mathematical subjects using graph theory; and a modularity-based filtering approach for network immunisation.;

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Guide to Graph Algorithms

comparative analysis of sequential, parallel and distributed graph algorithms - including algorithms for big data - and an investigation into the;

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Complex Network Analysis in Python

Construct, analyze, and visualize networks with networkx, a Python language module. Network analysis is a powerful tool you can apply to a;

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Mastering Python Forensics

this hands-on guide to using Python for forensic analysis and investigations Who This Book Is For If you are a network security;

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Introduction to Python Network Automation

bottom and by the time you have completed this book, you will at least reach the intermediate level of Python coding for enterprise networking;

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Introduction to Python Network Automation

and by the time you have completed this book, you will at least reach the intermediate level of Python coding for enterprise networking;

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Analysis of Complex Networks

Mathematical problems such as graph theory problems are of increasing importance for the analysis of modelling data in biomedical research;

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Mastering Python Networking

networking tasks using Python with ease * Use Python for network device automation, DevOps, and software-defined networking * Get practical;

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Quantitative Graph Theory

distance) Graph measures to characterize graphs quantitatively Applications of graph measures in social network analysis and other;

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Quantitative Graph Theory

distance) Graph measures to characterize graphs quantitatively Applications of graph measures in social network analysis and other;

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Algebraic Graph Algorithms

This textbook discusses the design and implementation of basic algebraic graph algorithms, and algebraic graph algorithms for complex;

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Python Data Analysis -

is for those who wish to learn different data analysis methods using Python 3.5 and its libraries. This book contains all the basic ingredients;

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Statistical and Machine Learning Approaches for Network Analysis

for Network Analysis provides an accessible framework for structurally analyzing graphs by bringing together known and novel approaches on;

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Mastering Python for Networking and Security

scripting Discover various Python libraries for building and securing your network Understand Python packages and libraries to secure your network;

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