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Network Analysis in Python: Getting Started

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Artur Krochin

1:58:26

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  • 0101.Course Overview.mp4
    01:39
  • 0201.Module Outline.mp4
    01:20
  • 0202.Course Prerequisites.mp4
    01:37
  • 0203.Network Science vs. Graph Theory.mp4
    03:54
  • 0204.What Is NetworkX.mp4
    03:38
  • 0205.Manipulating Networks in NetworkX.mp4
    04:00
  • 0206.Graph Theory through NetworkX.mp4
    05:26
  • 0207.Accessing and Modifying Attributes.mp4
    01:45
  • 0208.Graph Storage Formats.mp4
    05:11
  • 0301.Module Outline.mp4
    01:17
  • 0302.Why Network Visualization.mp4
    03:05
  • 0303.Native Visualization in NetworkX.mp4
    06:03
  • 0304.Introduction to Bokeh.mp4
    02:56
  • 0305.Bokeh Plots and Tools.mp4
    04:09
  • 0306.Bokeh Visualizing Node Attributes.mp4
    03:54
  • 0307.A Primer on Visual Network Analysis.mp4
    09:37
  • 0401.Module Outline.mp4
    01:33
  • 0402.Why Centrality Measures.mp4
    02:23
  • 0403.Degree Centrality.mp4
    02:41
  • 0404.Closeness Centrality.mp4
    05:00
  • 0405.Betweenness Centrality.mp4
    05:45
  • 0406.Katz, Eigenvector, and PageRank Centralities.mp4
    07:25
  • 0407.Community Detection Girvan-Newman Algorithm.mp4
    04:59
  • 0408.Demo Detecting Communities in NetworkX.mp4
    03:44
  • 0501.Module Outline.mp4
    01:31
  • 0502.Motivating Embeddings.mp4
    06:42
  • 0503.Word2vec.mp4
    06:14
  • 0504.Node2vec.mp4
    07:48
  • 0505.Demo Node2vec.mp4
    03:10
  • Description


    Network science is an underutilized part of data science. This course will empower you to leverage the network data your company has. You'll learn about network wrangling and visualization, centralities, communities, and machine learning techniques.

    What You'll Learn?


      Companies have amassed terabytes of data that can be represented as networks. However, due to a lack of data professionals skilled in network methods, this data is being underutilized. The aim of this course is to fix that and empower you to be able to reason about and build products based on networks. In this course, Network Analysis in Python: Getting Started, you'll gain the foundational skills needed to analyze networks using Python. First, you'll learn about the origins of network science and its relation to graph theory, as well as practical skills in manipulating graphs in NetworkX. Next, you'll explore how to create beautiful and illustrative visualizations of networks using the native capabilities of NetworkX and Bokeh. Then, you'll deep dive into centrality and community detection algorithms. Finally, you'll enrich your machine learning toolbox by learning about network embeddings. By the end of the course, you'll have learned how to conduct your own analysis of networks, how to visualize networks, and even how to build an advanced friendship prediction engine using network science and machine learning.

    More details


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    Artur Krochin
    Artur Krochin
    Instructor's Courses
    Having worked in a variety of industries ranging from energy to telecommunications as a Data Scientist, Artur is now helping build the future of digital banking at Revolut, where his job is to design intelligent models to fight financial crime.
    Pluralsight, LLC is an American privately held online education company that offers a variety of video training courses for software developers, IT administrators, and creative professionals through its website. Founded in 2004 by Aaron Skonnard, Keith Brown, Fritz Onion, and Bill Williams, the company has its headquarters in Farmington, Utah. As of July 2018, it uses more than 1,400 subject-matter experts as authors, and offers more than 7,000 courses in its catalog. Since first moving its courses online in 2007, the company has expanded, developing a full enterprise platform, and adding skills assessment modules.
    • language english
    • Training sessions 29
    • duration 1:58:26
    • level preliminary
    • Release Date 2023/10/12