• Free Co-Working at the CLU Center on the Second Friday of Each Month

    CLU Center for Entrepreneurship

    The CLU Center for Entrepreneurship has been a great friend to the Westlake Village Data Science Meet Up providing us with free meeting space for our monthly meeting. Now they've extended an additional offer just to our members to come and co-work with them for free on the second Friday of each month (typically the Friday following our monthly Meet Up). Greg Monterrosa, the Community Relations Manager for the Center has extended us this offer to come in for the day, work, meet the other entrepreneurs on site, learn about the Center's support programs for start ups, and generally feel the energy of being surrounded by like minded folks. There's no formal program and no need to register or even RSVP, just show up. You can check in with the receptionist in 105 or just hang out in the common spaces. Obviously there's free WiFi. If you want more detail just ask for Greg and he'll fill you in. Come for an hour or stay for the day.

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  • Using Graphs to Expose Corruption from Some of World's Largest Data Leaks

    CLU Center for Entrepreneurship

    Data Engineers and Scientists are always intrigued by new data sources. From spreadsheets and SQL to No-SQL sources such as MongoDB and XML. We will hear from Neo4j, provider of a native graph (think network) database. As any practitioner of AI and Machine Learning knows, relationships provide critical insights to our understanding and forecasting capabilities. Learn how you can leverage these insights to work for you. With the assistance of Neo4j's graph experts, the International Consortium for Investigative Journalism won the Pulitzer Prize for exposing the complex relationships hidden away in the Panama Papers (largest data breach of unstructured data) of the wealthy, their money, government officials, and tax havens. Neo also provided them with expertise for analyzing the subsequent Paradise Papers. More recently, Neo helped MSNBC use graph techniques to successfully identify the Russian Trolls responsible for over 200k fake tweets during the 2016 election. Discover the techniques used in these projects and how they are being used successfully by many global organizations for their cybersecurity, identity resolution, and fraud use cases. SPEAKER BIO Justin Fine is based in Los Angeles, CA and is a Field Engineer working mainly in the SoCal region. His academic background is applied mathematics and has worked with graphs for over 12 years in many different verticals while consulting (federal, telecoms, financial, etc). During this time as a consultant his focus was mainly advanced analytics utilizing NoSQL technologies. He recently comes from Microsoft's Azure team where he was a Data Solution architect and is very excited to be part of the Neo4j family! When Justin isn't nerding he enjoys scotch, cigars, and reading with his cat Penny.

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  • Machine Learning for Fraud Detection

    CLU Center for Entrepreneurship

    Entrepreneurs and organizations across all industries currently deploy AI-based fraud detection tools to save millions of dollars annually in lost revenue. These tools leverage advanced statistical techniques to alert stakeholders of potentially suspicious activity by identifying anomalies -- which are rare items, events or observations that differ significantly from the majority of the data. In this brief talk, we will overview the current landscape of automated tools available for business to combat fraud. In particular, we will focus on how modern, cloud-based technology has made it easier than ever for businesses to make smarter decisions based on data. About our Speaker Michael Johnson is a Data Scientist at at Aviana Global Technologies with over 6 years experience designing and implementing quantitative research strategies. His background includes two master’s degrees and deep knowledge of a wide variety of business problems relevant to applied statistics. In addition, he is an active member of the American Statistical Association and is an Amazon AWS Certified Cloud Practitioner.

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  • Free Co-Working at the CLU Center on the Second Friday of Each Month

    CLU Center for Entrepreneurship

    The CLU Center for Entrepreneurship has been a great friend to the Westlake Village Data Science Meet Up providing us with free meeting space for our monthly meeting. Now they've extended an additional offer just to our members to come and co-work with them for free on the second Friday of each month (typically the Friday following our monthly Meet Up). Greg Monterrosa, the Community Relations Manager for the Center has extended us this offer to come in for the day, work, meet the other entrepreneurs on site, learn about the Center's support programs for start ups, and generally feel the energy of being surrounded by like minded folks. There's no formal program and no need to register or even RSVP, just show up. You can check in with the receptionist in 105 or just hang out in the common spaces. Obviously there's free WiFi. If you want more detail just ask for Greg and he'll fill you in. Come for an hour or stay for the day.

  • Free Co-Working at the CLU Center on the Second Friday of Each Month

    CLU Center for Entrepreneurship

    The CLU Center for Entrepreneurship has been a great friend to the Westlake Village Data Science Meet Up providing us with free meeting space for our monthly meeting. Now they've extended an additional offer just to our members to come and co-work with them for free on the second Friday of each month (typically the Friday following our monthly Meet Up). Greg Monterrosa, the Community Relations Manager for the Center has extended us this offer to come in for the day, work, meet the other entrepreneurs on site, learn about the Center's support programs for start ups, and generally feel the energy of being surrounded by like minded folks. There's no formal program and no need to register or even RSVP, just show up. You can check in with the receptionist in 105 or just hang out in the common spaces. Obviously there's free WiFi. If you want more detail just ask for Greg and he'll fill you in. Come for an hour or stay for the day.

  • Insights Into Data Infrastructure Behind Algorithmic High Frequency Trading

    CLU Center for Entrepreneurship

    Overview of Our Talk Massive data volumes, low-latency, and complex processing capabilities are common characteristics of high frequency trading and analysis environments. Financial firms have a growing need to collect, store, and analyze more data than ever before. Tick data analysis helps firms keep sight of their investments and quickly react to market change to maximize profits. Such analysis requires a powerful database and storage solution to handle real-time and historical data sets. This talk describes the data flow of a typical trading platform, the database application and some data sets available for tick data analytics as well as storage architecture and some industry benchmarks to be aware of. About our Speaker Boni Bruno is the Chief Solutions Architect at Dell EMC and an Evangelist for Big Data Analytics, Edge Computing, Machine Learning, Data Security, and Hyper Converged. He is responsible for developing analytics and big data solutions around Dell EMC Emerging Technologies Product Portfolio as well as establishing various business initiatives with alliance partners around analytic solutions/product integration. Boni also has extensive experience in information security - cyber threat intelligence platforms, lawful intercept, security analytics, etc. He speaks regularly at conferences and is an evangelist for Digital Transformation for Businesses, Information Security, and Machine Learning.

  • Exploring Automated Modeling with H2O’s Driverless AI

    CLU Center for Entrepreneurship

    Overview of Our Talk As the adoption of ML in solving business use-cases has increased, there are often multiple unknowns that Machine Learning Scientist struggle with. To be effective in practice, it would be great to have an automated modeling engine which could help with feature engineering, hyper parameter tuning and model selection within a fixed computational budget (defined by Accuracy, Time and Interpretability). In this hands-on session, we will explore the usefulness of auto-modeling using real datasets related to supervised learning problems(Classification/Regression/TimeSeries). We will also discuss on how we can further explore and validate these automated models using model diagnostics and interpretation by enabling, 1. Model Validation: Ways to explore and validate black box ML systems enabling model comparison both globally and locally - identifying biases in the training data through interpretation. 2. Interpretable Models: Ability to build natively interpretable models - with the goal to simplify complex models to enable better understanding. 3. What-if Analysis: An interactive environment where communication can happen i.e. enable learning through interactions. User having the ability to conduct "What-If" analysis - effect of single or multiple features and their interactions 4. Model Debugging: Ways to analyze the misbehavior of the model by exploring counterfactual examples(adversarial examples and training) About our Speaker Our speaker, Pramit Choudhary, is an Applied Machine Learning Research Scientist/Engineer and currently Lead Data Scientist @h2o.ai. His area of interest is building scalable Statistical/Machine Learning models(Bayesian and Frequentist Modeling techniques) to help businesses realize their data-driven goals. Recently, he has been exploring better ways to understand and explain model's learned decision policies to reduce the chaos in building effective models to close the gap between a prototype and operationalized model(prescriptive Machine Learning). In his past life he has worked on ML problems related to NLP (e.g. topic modeling), improving operation efficiency in Oil and Gas Industry (e.g. time series/ anomaly detection), social media analysis, personalized recommendation engines, match-making and fraud detection to name a few

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  • Free Co-Working at the CLU Center on the Second Friday of Each Month

    CLU Center for Entrepreneurship

    The CLU Center for Entrepreneurship has been a great friend to the Westlake Village Data Science Meet Up providing us with free meeting space for our monthly meeting. Now they've extended an additional offer just to our members to come and co-work with them for free on the second Friday of each month (typically the Friday following our monthly Meet Up). Greg Monterrosa, the Community Relations Manager for the Center has extended us this offer to come in for the day, work, meet the other entrepreneurs on site, learn about the Center's support programs for start ups, and generally feel the energy of being surrounded by like minded folks. There's no formal program and no need to register or even RSVP, just show up. You can check in with the receptionist in 105 or just hang out in the common spaces. Obviously there's free WiFi. If you want more detail just ask for Greg and he'll fill you in. Come for an hour or stay for the day.

  • Beyond Moneyball: Applying Learnings from Sports Analytics

    CLU Center for Entrepreneurship

    Overview of Our Talk The world of sports analytics took off in the late 90s and hasn’t stopped. But what propelled it early on, and what creates the advantages certain organizations and players have today, is not what most data scientists are focused on. In fact, most resources spent on data science in the sports industry are being used with staggering low inefficiency and ROI. Taking a broader look at the lessons from the sports analytics movement, it’s apparent how much data science, in almost all industries and fields, can be improved by basic changes to approach and thinking. From entrepreneurs to fortune 500 companies, the greatest advantages moving forward will be shaped not by marginal improvements to gradient boosting and black box models, but by more optimally targeting problems long overlooked and misunderstood. About our Speaker Our speaker, Trevor Thoma, graduated from UCLA with a degree in statistics before becoming an analyst in the analytics department of the Orlando Magic basketball team. While there, he developed a metric to improve upon the predictive accuracy of the most advanced plus minus metric in the NBA: RPM. Afterward he worked in golf analytics, using data science as well as motor learning and biomechanics, to improve professional golfers’ performance in practice and on the course.

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  • Free Co-Working at the CLU Center on the Second Friday of Each Month

    CLU Center for Entrepreneurship

    The CLU Center for Entrepreneurship has been a great friend to the Westlake Village Data Science Meet Up providing us with free meeting space for our monthly meeting. Now they've extended an additional offer just to our members to come and co-work with them for free on the second Friday of each month (typically the Friday following our monthly Meet Up). Greg Monterrosa, the Community Relations Manager for the Center has extended us this offer to come in for the day, work, meet the other entrepreneurs on site, learn about the Center's support programs for start ups, and generally feel the energy of being surrounded by like minded folks. There's no formal program and no need to register or even RSVP, just show up. You can check in with the receptionist in 105 or just hang out in the common spaces. Obviously there's free WiFi. If you want more detail just ask for Greg and he'll fill you in. Come for an hour or stay for the day.