2022
John Elder spoke on a presenting panel at the KNIME Fall Summit
Data analysis brings value to every industry and line of business. Join John Elder in Austin, TX or online for the KNIME Fall Summit to deepen your data science skills and make a bigger impact on your organization.
Hear from business leaders in data science on novel data-driven approaches to problem solving. Take a full-day data analytics or data engineering course and then add on a morning workshop – from automating spreadsheets, to building Python nodes directly in KNIME, to building ML applications.
[11-14-2022]
Ramon Perez, AI Solutions Director, is part of a panel presenting session,
5C: Deployment of Wireless, Networked, Remote and Artificial Intelligence Technology
Pandemic-related disruptions and accelerating retirements of experienced personnel have led to operation-, maintenance- and commissioning-related challenges at hydropower sites. Implementation of wireless, secure remote access and AI solutions can address these issues. Come interact with industry experts regarding technology and applications for resolving these difficult issues. Bring your questions and experiences related to application of wireless and remote sensing/control and remote support/troubleshooting.
Ramon will be presenting with Christopher Chong, President & CEO – SST Wireless Inc. and Kaspar Vereide, Hydraulic Engineer – Sira-Kvina.
For more information on the conference visit Hydrovision International 2022.
[07-14-2022]
John Elder to Teach "The Best of Predictive Analytics" Workshops at Machine Learning Week 2022
The Best of Predictive Analytics: Core Machine Learning and Data Science Techniques
Monday, June 20, 2022 – Caesars Palace, Las Vegas
Full day: 8:30am – 4:30pm PDT
Workshop Description
This one-day session surveys standard and advanced methods for predictive modeling (aka machine learning).
Predictive analytics has proven capable of generating enormous returns across industries – but, with so many machine learning modeling methods, there are some tough questions that need answering:
- How do you pick the right one to deliver the greatest impact for your business, as applied over your data?
- What are the best practices along the way?
- How do you make it sure it works on new data?
In this workshop, renowned practitioner and hugely popular instructor Dr. John Elder will describe the key inner workings of leading machine learning algorithms, demonstrate their performance with business case studies, compare their merits, and show you how to select the method and tool best suited to each predictive analytics project.
Attendees will leave with an understanding of the most popular algorithms, including classical regression, decision trees, nearest neighbors, and neural networks, as well as breakthrough ensemble methods such as bagging, boosting, and random forests.
This workshop will also cover useful ways to visualize, select, reduce, and engineer features – such as principal components and projection pursuit. Most importantly, Dr. Elder reveals how the essential resampling techniques of cross-validation and bootstrapping make your models robust and reliable.
Throughout the workshop day, Dr. Elder will share his (often humorous) stories from real-world applications, highlighting mistakes to avoid.
If you’d like to become a practitioner of predictive analytics – or if you already are and would like to hone your knowledge across methods and best practices – this workshop is for you.
What you will learn:
- The tremendous value of learning from data
- How to create valuable predictive models with machine learning for your business
- Best Practices, with real-world stories of what happens when things go wrong
[06-20-2022]
Shree Taylor was a panel member at George Mason University's, Acquisition Next: Artificial Intelligence Symposium
The event features two panels composed of industry and government experts, Buying AI: Industry Challenges and Buying AI: Current Government Practices, as well as lunch, a keynote speaker, opportunities to network, and tours of the Institute for Digital InnovAtion facilities. The two discussion panels will be led by knowledgeable moderators to create a rich, interactive environment for speakers and registrants.
The first panel, Buying AI: Industry Challenges, will discuss the challenges of AI procurement from an industry perspective. This panel consists of representatives from both small and traditional firms who will speak about their challenges as developers and suppliers of AI tools purchased by the U.S. government.
Panel Members:
- Dr. Shree Taylor – Vice President of Government Analytics & Innovation at Elder Research Inc.
- Josh Wilson – Senior Vice President of Services and Technology at LMI
- Alexis Bonnell – Senior Business Executive: Emerging Technology Evangelist at Google
- Kristen Summers – Business Unit CTO at Microsoft Federal
Moderator: Benjamrin McMartin, Esq. – Senior Fellow at GMU Center for Government Contracting
The second panel, Buying AI: Current Government Practices, will focus on current practices used by U.S. government agencies to purchase AI tools. This panel is composed of government representatives who can offer first-hand accounts of the evolving state of AI acquisition and adoption in the federal government. Both panels will touch on topics central to the symposium theme, including intellectual property issues, ethics, and cyber-security concerns.
Panel Members:
- Major Andrew Bowne – Chief Legal Counsel at DAF-MIT AI Accelerator
- Azza Jayaprakash – Counsel at Intellectual Property Cadre at the Office of the USD (Acquisition & Sustainment), U.S. Department of Defense
- COL Matthew Benigni, PhD – Chief Data Officer and Director, Data and Decision Sciences Directorate (DDSD) at U.S. Army Futures Command
- Deniece Peterson – Sr. Director of Federal Market Analysis at Deltek
Moderator: Dr. Jerry McGinn – Executive Director at GMU Center for Government Contracting
For more information and to register, visit: Acquisition Next: Artificial Intelligence
[05-05-2022]
Grant Fleming to present AI Alignment Considerations for Data Science Practitioners
Grant Fleming to present AI Alignment Considerations for Data Science Practitioners
Accounts of AI algorithms making biased, unfair, or otherwise harmful predictions are capturing growing attention from the media, institutional researchers, and the public at large. In the vast majority of cases, these harmful predictions arise as the unanticipated and unintended consequence of using large, highly complex model to solve poorly specified tasks. Research around solving this “AI alignment problem” between the results desired and actually produced is quite nascent. Fortunately, this research has already yielded some best practices and software tools that practitioners can begin utilizing in their own workflows. This session will discuss a selection of best practices and software tools to mitigate the risks of harmful predictions in certain classification and NLP contexts.
For more information about this event and UMBC’s Data Science program.
[03-04-2022]