On September 28-30, the Graph + AI World 2020 conference will be held for people who are not indifferent to graph technologies and machine learning. The event will be held online for three days, participation is free.
The organizer was TigerGraph , the creator of the eponymous Grafova DB, and the program will include reports from speakers from various companies: Intel, KPMG, AT&T, Forbes, Intuit, UnitedHealth Group, Jaguar Land Rover, Xilinx, Xandr, Futurist Academy, etc.
Why participate to the Head or an Engineer and join one of 3000 members from 110 Fortune 500 companies? Welcome to cat.
For those who want to take part right away, the registration link .
The Graph + AI World conference aims to improve the efficiency of AI and machine learning projects through the use of Graph Algorithms.
Why Graph Algorithms?
We use graph databases every day and are probably not aware of it. Facebook, Instagram and Twitter use graph databases and analytics to understand how users relate to each other and link them to the right content. Every time you do a Google search, you are using the knowledge graph from Google. Product recommendations on Amazon - “people who bought this product also bought ...” or “these products are often bought together”? All this is also associated with analytical queries to graph databases.
If we compare different types of databases, we can highlight the main trends:
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Thus, if your data has many connections with each other, it is logical to use Graph databases instead of multiple Join queries, which will not be so efficient on large volumes. Besides, nobody canceled Graph Theory for Data Science;)
Key speakers
- UnitedHealth Group has created the largest Graph Database in the healthcare industry to communicate, analyze and provide real-time advice on treatment trajectories for 50 million patients.
- Jaguar Land Rover has reduced the request time for its complex supply chain model from 3 weeks to 45 minutes, allowing them to plan accurately and quickly respond to supply and demand uncertainties due to the Covid-19 pandemic.
- Intuit is using the knowledge graph as a fundamental technology for an AI-driven expert platform.
Program
The conference has a stellar agenda, filled with training and certification sessions on September 28 (pre-day) and business cases, use cases, and technical sessions on September 29 and 30. Some of the sessions are highlighted below.
28 September
Introduction to Graph Algorithms for Machine Learning Certification
Graph algorithms are essential building blocks for related data analysis and machine learning to gain a deeper understanding of that data. Graph algorithms can be used directly for unsupervised learning or for enriching training samples for supervised learning. This lesson will introduce the new TigerGraph training and certification program for applying Graph Algorithms to Machine Learning: content review, video, demo and certification process.
Hands-on Workshop: Accelerating Machine Learning with Graph Algorithms
In this workshop, you will be able to apply several different approaches to machine learning with graph-based data.
After setting up your graph database (in the cloud and free), we will do the following:
- Unsupervised Learning Using Graph Algorithms
- Feature Extraction and Graph Enrichment
- External training and integration with notebooks
- In-database ML techniques for graphs
We will have several datasets for different cases.
September 29
Application of Graph Model in Fintech and Risk Management
FinTell has built a graph with tens of billions of edges and nodes based on 1.5 billion active mobile devices per month. The graph model helps FinTell deliver superior quality risk management services to financial institutions.
Building a State of the Art Fraud Detection System with Graph + AI A
step-by-step guide and demonstration of what analytics can be quickly created with graph analytics on modest computing resources and how fraud-fighting performance improves by reducing missed fraud incidents AND reducing false positives of positives in a standard machine learning pipeline.
Executive Roundtable - Transforming Media & Entertainment With Graph + AI
Graph databases are used to identify, link and combine duplicate customer entities to create a single 360 ​​° profile. This usually translates into higher returns as a result of more accurate and effective recommendations for products and services. Join the executives at Ippen Digital and Xandr (part of AT&T) to learn how graphs and machine learning are changing the media and entertainment landscape.
September 30th
Supply Chain & Logistics Management with Graph DB & AI
Industrial manufacturing faces major challenges with the sheer volume of parts, components, and materials that must be procured from a multitude of globally distributed suppliers and then processed and assembled at multiple stages, making it much more difficult to track from supplier to the final product. This also includes logistics, i.e. types of transport, locations, duration, cost, etc.
By leveraging Graph Databases to provide transparency for complex and distributed data, coupled with predictive analytics, manufacturers can effectively address these challenges. Simultaneously optimizing production planning: ensuring parts availability, minimizing quality loss, improving assembly and overall delivery.
Recommendation Engine with In-Database Machine Learning
Recommender systems are used in various services such as video streaming, online shopping, and social media. In industrial applications, a database can contain hundreds of millions of users and items. Training the model in the database also avoids exporting the graph data from the DBMS to other machine learning platforms, and thus better maintain a continuous update of the recommendation model on changing training data.
Also at the conference, the results of the Graphathon 2020 hackathon will be announced .
registration
To participate in the free conference, you must register on the official event page using the link .
Join Graph + AI World!
See you at the conference.