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Big Data [clear filter]
Saturday, October 20
 

10:00am PDT

Predictive Analysis of Financial Fraud Detection using Azure ML and Spark ML in AWS
This talk aims at providing insights, performance, and architecture on Financial Fraud Detection on a mobile money transactional activity in Azure ML and Spark. We have predicted and classified the transaction as normal or fraud with a small sample and massive data set using Azure ML and Spark ML, which are traditional systems and Big Data respectively. I will present predictive analysis with several classification models experimenting in Azure and Spark ML. Besides, scalibility of Spark ML will be presented for the models with different number of nodes for Spark clusters in Amazon AWS.

Speakers
avatar for Jongwook Woo

Jongwook Woo

Professor, California State Univerisity Los Angeles & Big Data AI Center
Dr Jongwook Woo received his Ph.D from USC and went Yonsei University. He is a Professor at CIS Department of California State University Los Angeles and serves as a Technical Advisor of Isaac Engineering, Council Member of IBM Spark Technology Center and as a president at KSEA-SC... Read More →


Saturday October 20, 2018 10:00am - 10:30am PDT
Ballroom # 408A

10:30am PDT

An Opensource Data Governance System for IoT Communities
The I3 (Intelligent Internet-of-Things Integrator) Consortium is a newly formed open consortium being created to encourage the accelerated formation of community-based IoT networks. These networks are formed when independent IoT device owners work together to create data “rivers” that have more composite value than a series of individual IoT data streams. I3 is an innovative IoT data management system was first conceived at USC and evolved with encouragement from the City of Los Angeles and other entities seeking to create an ecosystem that will encourage the accelerated deployment of IoT technology by creating an environment that allows citizens and businesses to form community managed data marketplaces. This presentation will cover the challenges that must be overcome to realize what is, in effect, an open data market place that allows producers and consumers to connect and exchange data on mutually acceptable terms. The presentation will also cover the motivational issues that have driven the program with a focus on the implications such a system has for the larger IoT market. To close the session, a number of use cases will be presented that serve to illustrate application of the system in a live IOT environment.

Speakers
avatar for Jerry Power

Jerry Power

Executive Director, Institute for Communications Technology Management, University of Southern California
Jerry Power is the Executive Director of The Institute for Communication Technology Management (CTM) at The University of Southern California’s Marshall School of Business.  CTM is actively engaged in identifying, understanding, and leveraging emerging trends driven by the rapid... Read More →


Saturday October 20, 2018 10:30am - 11:00am PDT
Ballroom # 408A

1:00pm PDT

Practical Aspects of Machine Learning Models
Deep learning techniques are rapidly gaining popularity in a variety of industries. Developing accurate forecasting models can guarantee success in a corporate environment. Specifically, accurate demand prediction can empower decision making and expand vital planning capabilities of a company. These models can allow better negotiation on flexible shipping rates, as well as avoiding premium fees.
This talk will go over an industry use case that focuses on forecasting using both classical and modern machine learning techniques. The practical aspects of model building process will be discussed: utilizing the CRISP-DM approach and communicating results at the executive level.

Speakers
avatar for Inga Maslova

Inga Maslova

Professor, University of Southern California
Inga Maslova is a data scientist specializing in predictive analytics, machine learning, big data, and applications to finance, business analytics, economics, hydrology, remote sensing, precision agriculture, and climate change problems. She is currently teaching at Marshall School... Read More →


Saturday October 20, 2018 1:00pm - 1:30pm PDT
Ballroom # 408A

1:30pm PDT

AutoML - The Future of AI
The key challenge in making AI technology more accessible to the broader community is the scarcity of AI experts. Most businesses simply don’t have the much needed resources or skills for modeling and engineering. This is why automated machine learning and deep learning technologies (AutoML and AutoDL) are increasingly valued by academics and industries. The core of AI lies in the model design. Automated machine learning technologies reduce the barrier to AI application, enabling developers with no AI expertise to independently and easily develop and deploy AI models. Automated machine learning is expected to completely overturn the AI industry in the next few years, making AI accessible to everyone

Speakers
avatar for Ning Jiang

Ning Jiang

CTO, OneClick.ai
Ning Jiang is CTO of oneclick.ai, a leading platform in automating deep learning model design and deployment. Ning has over 15 years of experience in Machine Learning across multiple industries, including web/entity search, search ads, online retail, and cyber security. His was a... Read More →


Saturday October 20, 2018 1:30pm - 2:00pm PDT
Ballroom # 408A

2:00pm PDT

Modernizing and Digitally Transforming Traditional Industrial Companies Using IoT and AI
Most companies today are still relying on traditional assets -- equipment and people -- and outdated business models to compete in an highly dynamic, disruptive industry landscape. In this talk, presenter will describe in in detail, an actual recent client case study where he helped a $1.5B traditional B2B services company which owns over one million "machines" and 100K+ clients to move to a IoT and AI based business model to both generate new $250M earnings (both new sources of revenue and operational cost savings), and in doing so, begin to serve 20M consumers (i.e., also become a B2B2C company), and in the process, transform from a traditional blue collar service company to a modern, data-driven digital company. The presentation will include details examples of use of IoT, advanced data science, AI (Machines Learning, Predictive Analytics) across broad areas of the project.

Speakers
avatar for Sugath Warnakulasuriya

Sugath Warnakulasuriya

Managing Director, Thalamus Labs
Dr. Sugath Warnakulasuriya, Managing Director of Thalamus Labs, is a strategic advisor and entrepreneur with 25+ years of experience in innovation and growth for enterprises and startups. He has been a consultant with McKinsey & Co, and co-founded two companies: 10EQS and eLink Commerce... Read More →


Saturday October 20, 2018 2:00pm - 2:30pm PDT
Ballroom # 408A

2:30pm PDT

Big Data for the Rest of Us
Its an exciting time in the Big Data and Machine learning space! Never before has there been such an abundance of open-source tools and projects available for companies to leverage when they build their big data solution.


Leveraging the correct framework can significantly accelerate the development of a big data solution, making it simplicity for small teams to develop solutions that scale to terabyte data sets with relative ease. However, it is important to understand that each of the available frameworks are targeted at addressing specific pain points, that may, or may not, be relevant to your specific requirements and environment. The use of poorly suited frameworks, at best, provide little benefit to development and potentially introduces significant unnecessary complexities and downstream limitations.


In this presentation we highlight key factors to consider when developing a big data architecture, discuss the applicability of different big data frameworks to design around and the benefits and pitfalls associated with many of the common frameworks.

Speakers
avatar for Lawrence Spracklen

Lawrence Spracklen

VP of Engineering, SupportLogic, Inc.
Dr. Lawrence Spracklen leads engineering at SupportLogic, where he leads a team applying AI to the enterprise technical support space. Prior to joining SupportLogic, Lawrence lead engineering teams at two other ML startups; Alpine Data and Ayasdi. Before this, Lawrence spent over... Read More →


Saturday October 20, 2018 2:30pm - 3:00pm PDT
Ballroom # 408A