Big Data Ignite

11/16/2021

Our Event Sponsor, The Home Depot, is hiring Technologists and Data Science professionals nationwide! Explore open roles here: https://careers.homedepot.com/technology

Did you miss their two talks during BDI 2021? Check out the recordings below:

—The Home Depot EDW Journey to Google Cloud Platform (Lisa Barber, Sr Manager, Data & Analytics): https://youtu.be/QBf7ywaHsEI

—Interpretable Methods for Identifying Product Variants (Becky West, Senior Data Scientist): https://www.youtube.com/watch?v=UYmtF3pH0G4

The Home Depot’s technology associates expand our capabilities, write 90% of our code, and work closely with customers, learn more about our jobs.

11/10/2021

We would like to thank Confluent for supporting Big Data Ignite 2021 as a Gold Sponsor! You can learn about their work with “Data in Motion” through the following ways:

1. Check out this year’s talk by Patrick Druley: https://www.youtube.com/watch?v=Nx-oqcx93ZE

2. Visit the Confluent Blog and get engaged in the conversation: https://www.confluent.io/blog/

3. Explore the Confluent Community: https://launchpass.com/confluentcommunity

Find technical tutorials, best practices, customer stories, and industry news related to Apache Kafka, Confluent, and real-time data technologies.

11/08/2021

We would like to offer a big ‘thank you’ to all of our sponsors for making Big Data Ignite 2021 possible! We are deeply grateful for their partnership in our mission to foster local and regional expertise in advanced computing technologies and practice. Please support these organizations that support us.

11/03/2021

Check out tomorrow's free and virtaul talk at noon ET on how to automatically identify product variants using constrained clustering and techniques by Becky West of The Home Depot.

Register at bigdataignite.org

11/01/2021

It's our LAST WEEK for Big Data Ignite 2021! Join us as we hear from two more speakers about putting ideas into action. Register at bigdataignite.org

On Tuesday, November 2nd we have Jing Liu, PhD from the University of Michigan Speaking about "Improving the Scientific and Societal Impact of Data Science Research".

Abstract: I will discuss two aspects of the work that I and colleagues carry out at the Michigan Institute for Data Science – enabling reproducible research to improve the scientific impact of data science, and promoting “Data for Social Good” through collaboration with government and community partners. As data science methods are becoming an integral part of scientific inquiry in many research fields and decision making in private and public sectors, a significant challenge is the reproducibility and reliability of research and analytics results. I will describe our work to help make the production of data insight transparent, traceable, and trustworthy. Academic researchers have a unique role to play as many organizations are putting a major focus on translating data insight into business decisions and policies. I will describe our initial “Data for Good” effort, the challenges we face and discuss how we might improve the collaboration between academic researchers and our public sector partners.

Then on Thursday, November 4th we have Becky West from The Home Depot discussing "Interpretable Methods for Identifying Product Variants".

Abstract: As customers increasingly turn to online shopping, it is vital to help them navigate the wide variety of product offerings found online. One important way customers navigate is by choosing amongst several product variants. For example, the customer may prefer a product in a specific color or quantity. Note, the product is the same, only its attribute is different. While it is important to inform the customer about all product variant options, companies that sell large numbers of products may have a hard time identifying all products where variants are available. In this talk, I will discuss how to automatically identify product variants using constrained clustering and NLP techniques.

10/29/2021

October is almost over but we are not! Our speaker series will continue through next week as we expand to two more talks before we close up for the year.

10/27/2021

Thursday's talk will focus on techniques of deep learning with large graph structures. A huge amount of data can be represented as large graphs include social media websites, chemical structures and networks. The talk will review various algorithms and approaches for learning from such large structures. Particular emphasis will be on Graph Neural Networks and current results using these networks will be presented.

Register at bigdataignite.org to attend "Auto-Encoders and Deep Neural Networks for Structural Classification" by Saroja Kanchi.

10/25/2021

Check out this week's lineup at !

bigdataignite.org

Title:
Tuesday 10/26 - AI Technologies to Support Smart City Infrastructure

Speakers:
Michael Farmer (Professor and Department Head of Computer Science, Kettering University)
Peter Stanchev (Professor of Computer Science, Kettering University)

Abstract:
There are many factors that contribute to the development of high-level concepts such as smart devices, smart cars, smart homes and even smart cities. In one hand it is inevitable that the advancements of handheld devices create the basis for realization of many smart technologies. This is due to the increase of computational power and minimization of electronics worldwide. On the other hand, the exponential increase of data according to different sources leads to a growing necessity for the development of adequate technologies that can clean, structure and analyze more and more data every day. This in turn leads to the creation of new smarter technologies, which have a profound impact on our everyday life.

In this talk we will focus on the advancements of smart technologies that form the smart city ecosystem.

The following topics using Smart Services will be discussed:
a) Image retrieval using high level semantic features based on extraction of low level color, shape and texture characteristics and their conversion into high level semantic features.
b) Machine learning, with regard to deep learning, helping to identify, classify, and quantify patterns in medical images.
c) Sensor fusion framework using human cognitive models combined with probabilistic models.

Title:
Thursday 10/28 - Auto-Encoders and Deep Neural Networks for Structural Classification

Speaker:
Saroja Kanchi (Professor of Computer Science, Kettering University)

Abstract:
Various learning tasks require dealing with graph data which contains rich relation between elements. Applications include chemistry and drug design, social networks, predicting protein interface, and classifying diseases demand etc. In this talk, a survey of current techniques of trends in structural classification will be presented. While there are powerful models available for learning with large graphs such as GNN, computation challenges must be overcome due to neighborhood explosion. GNN and its variations will be compared for performance and accuracy of the models. Future research topics will be presented.

10/20/2021

Overwhelmed by all of the cloud analytics choices? Find out how you can adopt a multi-cloud approach with Confluent.

Join us for tomorrow's talk with Patrick Druley!

Details at bigdataignite.org

10/18/2021

Join us tomorrow for our first panel discussion of this year's conference! The event is free and virtual, so sign up at bigdataignite.org

10/13/2021

Data science is immature, evolving, and diverse, so the arc of a career in it is far from certain. TOMRROW, Michael Bloem will share some thoughts on how professionals can choose to lead and serve by embracing the evolving potential of data science and opportunistically making the most of this uncertain career path.

bigdataignite.org

10/12/2021

Within the last decade or two, emerged as a discipline. In Thursday's talk, Michael Bloem will share observations from four data science jobs: one in government research, a manufacturing enterprise, a data science consultant, and a large tech company.

Our speaker will also host an (ask me anything), so comment below with your data science question and we will ask it live!

Free and virtual registration at bigdataignite.org