• Join us for our first NC WiMLDS social!

    5311 S Miami Blvd

    NC WiMLDS is excited to announce our first NC WiMLDS Social! Thursday May 9th at 5pm. Stop by after work to enjoy a bite and/or beverage with friends and colleagues, and to meet other members of NC WiMLDS! Societa at 5311 Miami Blvd in RTP: http://societainfo.com/ NC WiMLDS membership is encouraged but not required. Everyone is welcome at WiMLDS events, so bring a friend! No agenda, no lesson plan, no instructors or mentors; this is a supportive space for the community. Also: NC WiMLDS has almost reached 1,000 members! Tell your friends and colleagues about NC WiMLDS - our 1000th member will get a prize! And look for additional NC WiMLDS summer events to be announced soon!

  • Why Health Care Needs Another OR (Machine Learning in Health Care series)

    UNC Health Care's Morrisville campus

    How you interpreted this title tells something about your perspective. If you work in health care you likely asked how an entire industry could need an operating room, while those who work in analytics and data science may wonder if some other kind of operations research field is emerging. Despite of its lack of understanding by the general public, the discipline of OR is a category of advanced analytics and a form of applied math with myriad useful applications. In this talk Polly will share the journey to bring OR into UNC Health Care with a case study around applications of discrete event simulation and optimization to improve patient throughput in hospitals. Polly Mitchell-Guthrie is the Director of Analytical Consulting Services within Enterprise Analytics and Data Sciences at UNC Health Care. Previously she was Senior Manager of the Advanced Analytics Customer Liaison Group in SAS’ R&D, where her team served as a bridge between R&D and external customers and internal SAS divisions. Before that she served in several other roles at SAS, after working in the nonprofit sector in philanthropy and social services. She has an MBA from the Kenan-Flagler Business School UNC Chapel Hill, where she also received her BA in Political Science as a Morehead Scholar. She has been active in the INFORMS professional association, including terms as the Chair and Vice Chair of the Analytics Certification Board and Secretary of the Analytics Society. She is one of the founders of the NC Chapter of WiMLDS.

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  • Partner event: Data + Women + Triangle Holiday potluck

    Data + Women + Triangle is hosting a holiday potluck. Come meet up with other people that support Women in Data, from data visualization to women who code - this meetup is all about bringing together the diverse group of women who have an interest in data and analytics in RTP and having a bit of holiday fun! Register with Data+Women+Triangle at https://www.meetup.com/DataPlusWomenPlusTriangle/events/256932850/ Here are the details, but make sure you register using this link: https://www.meetup.com/DataPlusWomenPlusTriangle/events/256932850/ This will be a potluck, bring a dish and/or bottle of wine, there should be plenty of food so if circumstances don't allow, just arrive with a smile. Please come by 630 to start the merriment and we'll have a fun group activity at 7 (drinking and eating allowed the whole time).

  • Introduction to Modern Machine Learning Techniques

    Introduction to Modern Machine Learning Techniques The tutorial describes fundamental concepts of machine learning algorithms and covers key elements of training powerful predictive models. We will discuss overfitting, hyper-parameter tuning, cross validation, regularization, feature engineering, information leakage and ensemble modeling. You will learn how to train and tune modern machine learning techniques such as gradient boosting, neural nets, and random forests, and how to interactively build machine learning pipelines. Speaker Bio: Funda Guneş does research and implements new data mining and machine learning approaches for SAS Visual Data Mining and Machine Learning. Her experience and research interests include combining well-established statistical methods with algorithm-based models, assessment and validation of machine learning models, efficient feature engineering techniques, regularization in machine learning algorithms, stacked ensemble models, and Bayesian statistical modeling. Through her work at SAS, she has given expository talks on new machine learning and data science techniques both internally and externally at major machine learning conferences, written technical papers and blog posts, and created short videos. In addition to machine learning, she is also an experienced statistician in clinical trials, survival analysis, mixed models, and longitudinal data analysis. Funda holds a PhD degree in Statistics from North Carolina State University. DIRECTIONS and INSTRUCTIONS: The MeetUp will be held in Building F, Room F101, which is in the training center on the SAS Campus. Here is a map to the SAS campus (https://dl.dropboxusercontent.com/u/103882174/CaryCampusMap.pdf). Parking is directly behind the building. Overflow parking is available in front of Building H (across the street from Building F). When you RSVP you will be asked to provide your first AND last name for SAS Security. SAS security will only allow people pre-registered to enter the campus. At the gate, give them your name and then follow the directions on the map to arrive at Building F. It is the first building on the right.

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  • How to Build Medical Scoring Systems (Machine Learning in Health Care series)

    UNC Health Care - Morrisville Conference Center (Carolina Ballroom)

    How do patients and doctors know that they can trust predictions from a model that they cannot understand? Transparency in machine learning models is critical in high stakes decisions, like those made every day in healthcare. Cynthia's lab creates machine learning algorithms for predictive models that are interpretable to human experts. As it turns out, by using modern optimization tools, one often does not need to sacrifice accuracy to gain interpretability. She will focus mainly on the problem of building medical scoring systems using data, which are sparse linear models with integer coefficients. She will also provide applications to ADHD diagnosis, sleep apnea screening, EEG monitoring for seizure prediction in ICU patients, and early detection of cognitive impairments. This is joint work with her former student Berk Ustun and several other collaborators. This work was a finalist for the 2017 INFORMS Daniel H. Wagner Prize, the winner of the 2017 INFORMS Computing Society Student Best Paper Award, and the winner of the 2016 INFORMS Innovative Applications in Analytics Award. Cynthia Rudin is an associate professor of computer science, electrical and computer engineering, and statistics at Duke University, and directs the Prediction Analysis Lab. Previously, Prof. Rudin held positions at MIT, Columbia, and NYU. She holds an undergraduate degree from the University at Buffalo, and a PhD in applied and computational mathematics from Princeton University. She is the recipient of the 2013 and 2016 INFORMS Innovative Applications in Analytics Awards, an NSF CAREER award, was named as one of the “Top 40 Under 40” by Poets and Quants in 2015, and was named by Businessinsider.com as one of the 12 most impressive professors at MIT in 2015. Work from her lab has won 10 best paper awards in the last 5 years. She is past chair of the INFORMS Data Mining Section, and is currently chair of the Statistical Learning and Data Science section of the American Statistical Association. She also serves on (or has served on) committees for DARPA, the National Institute of Justice, the National Academy of Sciences (for both statistics and criminology/law), and AAAI.

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  • Partner event: Analytics in Action: Trends You Need to Know

    SAS Executive Briefing Center

    • What we'll do Partner event, please do not register here but register at this link: https://www.elon.edu/u/academics/business/elon-business-analytics-conference/ This event is hosted by the Center for Organizational Analytics and the Martha and Spencer Love School of Business and led by Professor Haya Ajjan. Speakers include Radhika Kulkarni and Gayle Bieler, who have spoken to our MeetUp in the past. Master Business Practices - Learn from presentations by analytics experts on topics such as the changing landscape of analytics, predictive analytics, and the future of analytics. - Secure a cross-industry view of high-impact real-world analytics applications and learn how to apply them effectively. - Leverage analytics best practices to optimize your business processes and make fact-based business decisions. - Gain valuable insights that will help decision makers in your company better understand the value of analytics as a competitive driver. Advance Your Career - Improve your knowledge of the latest analytics trends. - Enjoy networking opportunities that provide future directions and contacts that can help you and your business. - Learn how to sell analytics to key decision makers and potential users. - Conduct a follow-up presentation for your company on best practices and innovative strategies that will open pathways to new possibilities. - Meet with Elon faculty and program administrators to learn about the accelerated M.S. in Management, Organizational Analytics program at Elon University. Agenda Time Session 7:30 – 9:00 Check-in/Registration 7:30 – 8:00 Continental Breakfast 8:00 – 8:05 Welcome Raghu Tadepalli, Dean, Love School of Business 8:05 – 9:00 The Data Science Revolution in Industry John Elder, Chair and Founder, Elder’s Research 9:00 – 10:00 Charting Collections of Connections in Social Media: Creating Maps and Measures with NodeXL Marc Smith, Founder, NodeXL 10:00 – 11:00 From Statistics to Data Science Startup: Transformation Within a Large Research Organization Gayle Bieler, Director, Center for Data Science, RTI International 11:00 – 12:00 Analytics at GM Tom Capotosto, Director, Advanced Analytics, General Motors 12:00 – 1:00 Lunch and Networking 1:00 – 1:45 Big Data and Big Analytics – Opportunities for Inter-disciplinary Innovation Radhika Kulkarni, VP, Advanced Analytics R&D, SAS Institute Inc. 1:45 – 2:45 Automating Machine Learning: A practical guide to AI adoption Jeff Holoman, Director of Sales for the Southeast, DataRobot 2:45 – 3:00 Networking Break 3:00 – 3:45 Transforming Your Business with AI Scott Langfeldt, Founder and CEO, APEX Data Science 3:45 – 4:00 Closing Remarks & Wrap-up Haya Ajjan, Associate Professor, Elon University • What to bring • Important to know

  • Partner Event: Triangle Machine Learning Day

    Duke University, Penn Pavilion

    • What we'll do This is a partner event, organized by Duke professor Cynthia Rudin, who always ensures parity of women speakers in events she plans. Member Melinda Thielbar will be one of the speakers. Sign up here: https://www2.cs.duke.edu/induke/tmld/2018/index.php Do NOT sign up here - we are only advertising this event, so there is no registration or wait list. • What to bring • Important to know

  • Partner Event: Research Triangle Analysts Annual Analytics Forward

    Blue Cross and Blue Shield of North Carolina

    • What we'll do This is an event organized by the Research Triangle Analysts' MeetUp, including WiMLDS member Melinda Thielbar. Analytics>Forward is happening again! Based on the "bar camp"-style conferences, the program will be set the day of the conference based on all of the exciting pitches you'll hear first thing in the morning. See https://www.meetup.com/Research-Triangle-Analysts/events/246678392/. • What to bring Bring your 50-minute talk and a stack of business cards for a day of mathy fun with all of your favorite analysts. • Important to know This year, they are very pleased to welcome Mara Averick (@dataandme on Twitter), as thekeynote speaker! Mara is an RStudio employee whose celebrated curation of data-science web posts has earned her almost 20,000 Twitter followers and enormous gratitude in the community. Mara’s talk will explore what she has learned about successfully communicating data science • Important to know Do not RSVP here or add your name to the waitlist -register on their site at https://www.meetup.com/Research-Triangle-Analysts/events/246678392/.

  • Partner Event: Livestream of Women in Data Science Conference w/free lunch!

    • What we'll do Partner event: Cisco and Data+Women+Triangle are livestreaming the Women in Data Science (WiDS) Conference (http://www.widsconference.org/about2018.html). Register with Data+Women+Triangle at https://www.meetup.com/DataPlusWomenPlusTriangle/events/247736717/ Here are the details, but make sure you register using this link: https://www.meetup.com/DataPlusWomenPlusTriangle/events/247736717/ Come hang out with fellow data scientistas at the Cisco campus for all or part of it. Thanks, Cisco, for providing lunch and snacks! LOCAL AGENDA 11:30 AM Doors open 12:00 PM Lunch served. 12:10 PM Livestream begins. 1:50 PM Jennifer Redmon and Tori Hall talk about data science at Cisco. 2:15 PM Livestream continues. 3:30 PM Cheese and snacks and networking the Data+Triangle+Women way. 5:00 PM Livestream continues. 8:00 PM End The conference aims to inspire and educate data scientists worldwide, regardless of gender, and support women in the field. This annual one-day technical conference provides an opportunity to hear about the latest data science related research and applications in a broad set of domains, All genders are invited to participate in the conference, which features exclusively female speakers. The 2018 program will feature fantastic speakers on a broad array of topics ranging from cybersecurity to astrophysics to computational finance, and more. Official schedule (all times PST) is here: http://www.widsconference.org/2018-schedule.html • What to bring Want to bring your laptop? You will be able to use guest wi-fi. Work remotely! • Important to know Thank you NC Women for Machine Learning and Data Science for the prompt. This goes until 8pm! Drop in and out as needed to network with other data scientistas. Non-Cisco employees will need to be escorted in and out, so signage on the Building 11 doors will have instructions about this the day-of. See you then! • What to bring Want to bring your laptop? You will be able to use guest wi-fi. Work remotely! • Important to know

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  • Data science in high-tech manufacturing, agriculture + fin-tech

    Event description: We have members who work in very diverse industries, so for this MeetUp we’ll hear from Irem, who works in high tech manufacturing; Laura, who works in fin-tech; and Angel, who works in agriculture. Each will share what kinds of projects they tackle, what it’s like to work in their industry, how they got into this field, and how they stay in touch with new developments. Our discussion will also be interactive, with time for questions from attendees as well. Come join us for a lively discussion with a great group of women! Look below for more information about their backgrounds. How to find the meeting: Please use the Lenovo visitor entrance. To do that, you will have to pass a large parking lot, which is for employees, and continue ahead. You will see the signs for Visitors Entrance and Executive Briefing Centers, where our room is located. Our panelists: Dr. Irem Sengul Orgut received her Ph.D. in Industrial Engineering with a minor in Statistics in 2015 from the Edward P. Fitts Department of Industrial and Systems Engineering at North Carolina State University. She currently works at Lenovo Data Center Group as Analytics Project Manager where she uses operations research and analytics methods in a wide variety of problems, including field quality prediction and proactive customer issue resolution. Prior to starting her doctoral studies, she received her B.S. degrees in Industrial Engineering and Mechanical Engineering from Bogazici University, Istanbul, Turkey, in 2010. Her areas of interest and expertise include stochastic and statistical modeling of complex systems with multiple objectives and conflicting decision makers. She received various awards for her research. She is a member of INFORMS and IIE. She lives in Raleigh, NC with her husband and one year old son. Dr. Laura Jackson is a principal data scientist at PrecisionLender, a commercial banking pricing & profitability platform. She creates visualizations that illuminate patterns and anomalies in banking data, and builds machine learning models that make smart recommendations to bankers, helping them balance their customer’s needs with the risk considerations of the bank. Laura’s sometimes-winding, never-boring career path began at William & Mary, where she earned a BS in mathematical economics and an MS in operations research. She then earned a PhD in computer science at North Carolina State University. Along the way, she completed a year-long stint as an actuary (CIGNA), and worked part-time for two years designing and simulating novel computer network architectures and protocols (Microcomputing Center of NC). Laura then joined Research & Development at SAS where she stayed for 11 years. In one role, she used sensor data from manufacturing systems (such as oil & gas refineries) to prevent catastrophic failures through early detection and predictive maintenance. In another, she estimated the frequency of operational risk loss events (such as fraud and natural disasters) to enable financial institutions to comply with solvency regulations. Angel Turner is a statistical scientist consulting in the agriculture and foresight space. She is the cofounder of the local AgBio AgTech MeetUp where professionals from diverse fields of life science, technology, engineering come together to break down barriers and innovate in agriculture. Angel holds a Master of Agriculture from Clemson University and has over 18 years in the agricultural industry traveling the path from field, to greenhouse research, lab work and data analysis. Most recently she spent 11 years as a Statistician with Monsanto where her analytic skills supported trait discovery research and model development to estimate plant metrics from imaging at Monsanto's 'Automated Greenhouse'. Angel is a continual learner committed to making agriculture more environmentally sustainable.

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