Data Driven Government Workshops Announced!

The workshops have been announced for Data Driven Government (formerly known as Predictive Analytics World for Government), Sep 25 in Washington, DC. Use the code KDNUGGETS for a 15% discount on your Deep Learning World ticket.

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Data Driven Government - Pre- & Post-Conference Workshops Announced!

Workshops announced!

The workshops have been announced for Data Driven Government! Formerly known as Predictive Analytics World for Government, this premier conference covers the emerging trends and best practices of how government agencies (at both Federal, State and local level) are currently using data analytics to enhance mission outcomes. 

Take a look at the workshops just announced!

Use the code KDNUGGETS for a 15% discount on your Deep Learning World ticket

** NEW! ** Fraud Analytics & Anomaly Detection

September 23rd, 2019 - 8:30 am - 4:30 pm

Dramatically reducing fraud and other abuse is a challenging task requiring a comprehensive and flexible analytics solution. Wherever your organization is along the wide spectrum of fraud analytics capabilities -- from basic rules and reporting to complex network graph analysis – this workshop will show you how to build out all the components of a holistic and robust fraud analytics platform. We will review critical technical details as well as problems to watch out for based on lessons learned over years of consulting on real-world fraud cases.

This one-day session teaches best practices for fraud analytics constrained by the realities of incomplete data and unrecognized or emerging fraud patterns. Existing fraud models have proven value, but nagging concerns remain about “unknown unknowns”.  A new view of the problem is required.

Attendees will learn how to:

  • Use new unsupervised learning techniques to identify previously unseen cases of fraud

  • Recognize and remove common biases

    (such as stemming from rare known fraud cases and from selection effects)

  • Prioritize anomaly types by their fraud likelihood

  • Incorporate multiple techniques and processes into an effective anti-fraud platform

About the Instructor:

Mike Thurber

Mike Thurber is the Lead Data Scientist in Elder Research's Commercial Analytics Group working across multiple teams and industries including finance, retail, energy, and telecom.  Mike’s primary focus is healthcare and insurance, where his projects range from predicting extreme payouts on long-term care claims, to identifying healthcare provider fraud, and measuring the effect of Cesarean delivery on infant health. His expertise in collaboration, data exploration, predictive modeling, rigorous testing, and removing biases common to algorithms, creates confidence in the actions recommended by the analytic products of his team.

The Best of Predictive Analytics: Core Machine Learning and Data Science Techniques

September 24th, 2019 - 8:30 am - 4:30 pm

This one-day session surveys standard and advanced methods for predictive modeling (aka machine learning). 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 innovative 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.

About the Instructor:

John Elder

John Elder Ph.D.

John Elder chairs America’s most experienced Data Science consultancy. Founded in 1995, Elder Research has offices in Virginia, Maryland, North Carolina, and Washington DC. Dr. Elder co-authored 3 award-winning books on analytics, was a discoverer of ensemble methods, chairs international conferences, and is a popular keynote speaker. John is occasionally an Adjunct Professor of Systems Engineering at the University of Virginia and was named by President Bush to serve 5 years on a panel to guide technology for national security.

** NEW! ** Data Science for Managers

September 26th, 2019 - 8:30 am - 4:30 pm

This 1-day workshop is an introduction to data science for executives and managers of data science programs. It provides a high-level overview of modern data science concepts, tools, and techniques from a management perspective. All stages of the data science lifecycle will be discussed in the context of agile management methodologies using real-world case studies. Managers will learn how to identify skilled data scientists and build data science teams that use sound scientific methods to meet their organization’s objectives. Leaders will learn to ask the right questions, solve the right problems, keep data science projects on track, ensure their solutions are deployed and avoid common pitfalls along the way. Both technical and non-technical participants will benefit from this workshop and be equipped with the knowledge necessary to lead effective data science programs in their organizations.

Participants will learn how to:

  • Understand fundamental concepts of data science

  • Plan and manage the data science project lifecycle using agile techniques

  • Define the appropriate data science problem to solve

  • Build effective data science teams within an organization

  • Avoid common pitfalls in data science management

About the Instructor:

Carl Hoover, Ph.D

Carl Hoover has led dozens of data science projects while working with the leading analytics firm Elder Research. His diverse experience includes work in security, counterintelligence, psychology, fraud, finance, insurance, pharmaceuticals, avionics, manufacturing, and robotics.  Most of his recent technical work involves triage and ranking models for human-centric prioritization tasks.  Over his decade of work with Elder, he's played just about every role in the data science lifecycle including data wrangler, scientist, tech lead, project manager, business manager, executive, and even client.  As Chief Technology Officer, Carl leads long-term technical strategy, manages an R&D portfolio and oversees a technical advisory committee focused on cutting-edge data science research and practice.  Carl is a contractor with the University of Missouri College of Engineering where he teaches graduate-level courses for NGA's Program of Study in Data Science.

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We look forward to seeing you at Data Driven Government!

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Conference produced by: Rising Media & Prediction Impact
Rising Media Limited