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Graph Algorithms for Data Science

             
                                                              
Jan 9, 2020 Sign up to like post                            
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Welcome to Graphs For Science, a newsletter dedicated to Graph and
Network Algorithms with applications to Data Science.

Graphs are simple concepts: a set of individual Nodes (components)
connected by Edges (relationships). In this very simplicity lies
their power. They can describe the structure of our friendships,
connections between airports, the spread of diseases from person to
person, the relation of one concept to another, how species interact
in an ecosystem or how computers communicate to form the World Wide
Web.

Networks are the fundamental language of our increasingly complex
world and the key to successfully understand it. By exploring in
detail the way graphs can be used to explore, describe, analyze and
understand empirical datasets we will put you at the forefront of
this growing field.

We plan to cover:

  * Graph representations

  * Search and Routing Algorithms

  * Airline Networks

  * Epidemic Spreading

  * Recommendation Systems

  * Node Embeddings

  * etc

Recent developments in online services and in data storage have made
an unprecedented amount of data available for our exploration. These
new datasets in combinations with the powerful new computational
tools of the Python Data Science ecosystem will allows us to explore
this fascinating field in an intuitive and hands-on way.

Twice a month we'll look in detail at a new graph algorithm by
implementing it from scratch and applying it to a specific dataset.

Sign up now so you don't miss the first issue.

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