Data Science Expo

Saturday, May 18th, 2019 | Pasadena Convention Center

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Deep Learning

Machine Learning

Predictive Analytics

Natural Language Processing

Data Visualization

AI Research

Presented By

Participation From

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Speakers

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Sophie Lellis-Petrie


Data Scientist

Warner Bros. Entertainment

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Sophie Lellis-Petrie


Data Scientist

Warner Bros. Entertainment

Combines descriptive and inferential statistics in order to have a holistic understanding of the data in order to fit the best models to the data. Has a Bachelor of Science in Statistics from the University of California, Los Angeles and pursuing Masters of Applied Statistics with strong foundation in statistics applied knowledge in capstone courses in multiple disciplines. Continues to grow statistics portfolio in the Work Force Analytics group in Warner Brothers.

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Joe Gardner


CEO

VentureDevs

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Joe Gardner


CEO

VentureDevs

Joe is a multi-time entrepreneur with eight years of experience founding, funding, growing, and selling technology companies. Joe’s experience as an investor, successful founder, and business operator has led him to create a prolific network of entrepreneurs, investors, and operators in the SoCal, Silicon Valley, and Northeast ecosystems. He is currently the CEO of VentureDevs and managing partner at Advantage Ventures.

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Patrick Prothro


Data Scientist

Latham & Watkins

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Patrick Prothro


Data Scientist

Latham & Watkins

There is an interesting story behind all data. Whether it be sports, education, etc. I'm always looking to find the meaning behind the numbers. Analyze, visualize, and explain what is going on behind the scenes. It's always been a passion of mine to find the unique answers to a puzzle with multiple solutions. Using data I've been able to find those unique answers that many may have overlooked in order to improve business efficiency.

My specialties include using a broad spectrum of software programs , advanced statistics, and an acumen for problem solving to find the answers buried in a company's data. I am currently an analyst at an E-Commerce Company and plan to enter the field of Machine Learning and Data Science.

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Jingyi Jessica Li


Assistant Professor

University of California

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Jingyi Jessica Li


Assistant Professor

University of California

Jingyi Jessica Li is an Assistant Professor in the Department of Statistics and the Department of Human Genetics at University of California, Los Angeles (UCLA). She is also a faculty member in the Interdepartmental Ph.D. Program in Bioinformatics and a member in the Jonsson Comprehensive Cancer Center (JCCC) Gene Regulation Research Program Area. Prior to joining UCLA in 2013, Jessica obtained her Ph.D. degree from the Interdepartmental Group in Biostatistics at University of California, Berkeley. Jessica received her B.S. (summa cum laude) from the Department of Biological Sciences and Technology at Tsinghua University, China in 2007. Jessica and her students focus on developing statistical and computational methods motivated by important questions in biomedical sciences and abundant information in big genomic and health related data. On the statistical methodology side, her research interests include association measures, high-dimensional variable selection, and classification metrics. On the biomedical application side, her research interests include next-generation RNA sequencing, comparative genomics, and information flow in the central dogma. Jessica is the recipient of the Hellman Fellowship (2015), the PhRMA Foundation Research Starter Grant in Informatics (2017), the Alfred P. Sloan Research Fellowship (2018), and the Johnson & Johnson WiSTEM2D Math Scholar Award (2018).

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Nick Acosta


Developer Advocate

IBM

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Nick Acosta


Developer Advocate

IBM

Before becoming an AI Advocate at IBM, Nick studied computer science at Purdue University and the University of Southern California, and was a high performance computing consultant for Hewlett-Packard in Grenoble, France. He now specializes in machine learning and interacting with other data scientists of various communities, startups, and enterprises in order to help them succeed on IBM’s data science platform. He has a strong interest in data science education and all things Kardashian.

Who Should Attend

The Data Science Expo is for data scientists, business analysts, researchers, educators, students, developers, and tool creators.

Data scientists

Developers and Programmers

Students

Educators

Business Analysts

Geeks

And MORE!

AGENDA


8:55AM - 9:00AM

Opening Remarks and Announcements


9:00AM - 9:25AM

The Interview Process of Becoming a Data Scientist - Patrick Prothro (Latham & Watkins)


9:30am- 9:55am

Boosting Your Model with Machine Learning - Sophie Lellis-Petrie (Warner Bros. Entertainment)


9:55AM - 10:15AM

Coffee Break


10:15AM - 10:40AM

The Right Way to Approach Data in Business - Joe Gardner (VentureDevs)


10:40AM - 11:05AM

How To Control The More Severe Type of Error in Binary Classification- Jingyi Jessica Li (UCLA)


11:05AM - 11:30AM

Harnessing Big Data to Make Healthcare Healthier - Brian Owens (BendCare)


11:30AM - 1:00PM

Lunch Break


1:00PM - 1:25PM

Choosing The Right Cloud: A Machine Learning Expo- Nick Acosta (IBM)


Get the latest news, offers, and more about the Data Science Expo and the topic of software development.

May 18th, 2019

Convention Center
Pasadena, CA