What we're about

Under the lead of international Data Science trends, technology innovations such as artificial intelligence, machine learning, robotics, nanotechnology, 3D printing, and biotechnology, are revolutionizing the global economic patterns. In order to comply with International Data Science innovation strategic vision and common development, Southern California Data Science 2016 Conference will be held to exhibit industry experts and scholars an in-depth academic and commercial feast in Data Science.

Southern California owns a huge excellent science and technology industry elites and leaders. Occupying a leading position in numerous global industries such as film entertainment, culture innovation, and digital media, Los Angeles owns enormous potential in Data Science application and development. Therefore, a worldwide influential Data Science Forum sponsored and created by professionals will be conventionally held in United Southern California, the global center of innovation and development.

Our mission is to fill in the blanks in Southern California discussions and exchange of Data Science. Our theme for 2016 is ‘Data Science Technology, Innovation, and Career’, focusing on the exchange of cutting edge technology, innovation in specific areas of industry and career settings in different companies.

Upcoming events (1)

An evening with Machine Learning Experts(REC. Sys, NLP, Modeling Financial Svcs)

Hi Everyone, Apologies for the delay, please find the agenda for the evening mentioned below, Agenda: 6:30 pm - 6:45 pm - Arrivals, eat/drink and network 6:50 pm - 7:30 pm - Best practices for building scalable Recommendation Systems by Vedant Dhandhania 7:30 pm - 7:50 pm - Introduction to building FAQ Chatbot by Bowen Chen 7:50 - 8:30: Predictive Modeling of Lapse Rates in Financial Services by Olaf and Tommy 8:30 pm - 9:00 pm - Networking 9 pm - Enjoy Venice Beach; hard stop 1. Topic: Best practices for building scalable Recommendation Systems Vedant Dhandhania - one of the best experts in the field of ML that I know of and a very humble guy. (https://www.linkedin.com/in/vedantdhandhania/) Vedant has been focused on building large scale recommendation systems for over 200 businesses. His passion lies between the intersection of Signal Processing and Machine learning. Earlier, Vedant used to lead the Data science efforts at Retention Science where his team build out over 30 predictive ML models for more than 300M users. The ML models include recommenders, lead scoring, churn prediction, LTV/CLV, AB testing, Bandits, Reinforcement learning for marketing applications Linkedin: https://www.linkedin.com/in/vedantdhandhania/ 2. Bowen Chen from Fair.com Title: Introduction FAQ Chatbot (NLP) I would like to give a short talk about building a FAQ chatbot to discuss the reasons why data scientists need to think, act and build like engineers. In the talk, I planned to share a quick tutorial on how to leverage the power of existing AI platforms to build a useful solution that drives value with very little code written, in turn proving organizations do not need to build everything from scratch to make an impact. 3. Title: Predictive Modeling of Lapse Rates in Financial Services: Statistical and Machine Learning approaches in theory and practice 1. Tommy Steed: Director Actuary / Product Design, Retirement Solutions Division, Pacific Life (https://www.linkedin.com/in/tommy-steed-fsa-04951541/) 2. Olaf Menzer: Sr. Data Scientist, Retirement Solutions Division, Pacific Life (https://www.linkedin.com/in/olaf-menzer-00871184/) Help our company look at potential new ways to model our policyholder lapse rate. We would like to investigate alternative methods to project policyholder behaviour as part of our financial projection models. These models combine in-force and new business projections under stochastic economic scenarios. Please do reach out if any question. Very excited for the next event. Location: 1314 Pacific Ave, Venice, CA 90291 Directions: Enter the building through the back (alley) entrance via Park Row Alley. You can enter the event space through the two middle doors of the building. Parking: Suggestion: - Arrive early find street parking close to the venue - Public Parking: https://goo.gl/maps/UyR1JyaX2eXiqnbL7. - If possible Uber or Lyft Will not be possible to provide dedicated parking this time. It's Venice :)

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