• Webinar: The 5 Key AI Takeaways for Today's C-Suite

    *THIS IS A VIRTUAL EVENT* Registration Please follow this link to reserve your seat: https://www.h2o.ai/webinars/?commid=362992 Description This discussion will explore real-world examples and how to democratize AI in your organization. 1. Build a Data science culture 2. Ask the right questions 3. Connect to the community 4. Technology considerations 5. Trust in AI Presenters: Ingrid Burton, H2O.ai & Vinod Iyengar, H2O.ai

  • Webinar: Extending the H2O Driverless AI Platform with Your Recipes

    *THIS IS A VIRTUAL EVENT, THERE WILL BE NO MEETUP AT 2307 LEGHORN IN MOUNTAIN VIEW ON 6/26/19* Registration Please follow this link to reserve your seat: https://www.h2o.ai/webinars/?commid=360533 Description Driverless AI is H2O.ai's latest flagship product for automatic machine learning. It fully automates some of the most challenging and productive tasks in applied data science such as feature engineering, model tuning, model ensembling and production deployment. Driverless AI turns Kaggle-winning grandmaster recipes into production-ready code (Java and C++), and is specifically designed to avoid common mistakes such as under- or overfitting, data leakage or improper model validation, which are some of the hardest challenges in data science. Other industry-leading capabilities include automatic data visualization and machine learning interpretability. We're now excited to add the ability for users, partners and customers to extend the platform with Bring-Your-Own-Recipe. Now domain experts and advanced data scientists can now write their own recipes and seamlessly extend Driverless AI with their favorite tools from the rich ecosystem of open-source data science and machine learning libraries. During this webinar we'll demonstrate how easy it is to write a new recipe for feature transformation or use a third party algorithm to extend Driverless AI. Speaker's bio Arno Candel is the Chief Technology Officer at H2O.ai. He is the main committer of H2O-3 and Driverless AI and has been designing and implementing high-performance machine-learning algorithms since 2012. Previously, he spent a decade in supercomputing at ETH and SLAC and collaborated with CERN on next-generation particle accelerators. Arno holds a PhD and Masters summa cum laude in Physics from ETH Zurich, Switzerland. He was named “2014 Big Data All-Star” by Fortune Magazine and featured by ETH GLOBE in 2015. Follow him on Twitter: @ArnoCandel.

  • Productionalizing ML at-scale with MLFlow and H2O Sparkling Water

    Galvanize - San Francisco

    Hello Makers! Join us this evening to hear from Alvaro Viloria of Groupon on how they are productionalizing machine learning at scale with MLFlow and H2O Sparkling Water. Following is a brief agenda for the evening: 6:00 - 6:30 PM: Doors open for networking and pizza 6:30 - 7:15 PM: Alvaro's talk 7:15 - 7:30 PM: Q&A Description: The conceptual workflow of applying machine learning (ML) to any specific use case is simple: at the training phase, the learning component takes a dataset as input and builds a learned model; at the serving phase, the model takes features as input and yields predictions. However, the actual workflow becomes more complex when ML models need to be set up in a production environment. This will require a careful orchestration of several components to reliably produce, deploy and evaluate such models. At Groupon, the ranking recommendation system is based on supervised ML models. Once a model is promoted from candidate to released, and start serving real-time traffic, it opens the following questions: How can we assure that the model is not losing its prediction power? How can we reliably keep track of all released models life cycle? To answer these questions, each new model is built on an ML pipeline that guarantees its standardization, transparency, reproducibility and reliable evaluation. For this purpose, at Groupon we built a custom made ML-pipeline, using a simple but powerful integration between MLFow and H2O sparkling water. Every model during its training step publishes all its information, such as output values, hyperparameters, evaluation metrics, features, queries, etcetera, into MLflow as the main Model Registry. As a final step of the ML Pipeline, every released model is evaluated with fresh data, by applying a sequence of orchestrated steps. Each released model retrieves its metadata from MLflow and is evaluated by using the same constraints over the data, so as to assure a reliable evaluation. Finally, the variations on the predictive power of the model are visualized using Kibana, to constantly monitor any sign of decay. Alvaro's Bio: Alvaro is a Software Engineer at Groupon, he can be reached on Linkedin here: https://www.linkedin.com/in/alvaro-viloria-97b4b725/ Looking forward to meeting you all!

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  • Graph-Based Business Intelligence

    Metis Data Science

    We are hosting this event as part of GlobalGraphCelebrationDay.com. To get added to the community graph for this event, please RSVP via: https://neo4j.typeform.com/to/USb6It?event=SF ----------------------------- Co-Hosted By: ----------------------------- https://www.meetup.com/Metis-San-Francisco-Data-Science/ https://www.meetup.com/San-Francisco-Big-Data-Science/ https://www.meetup.com/graphdb-sf/ ----------------------------- Talk Abstract ----------------------------- Graph databases are core big data technology. This adoption requires mainstream business to integrate with other business technologies, such as Business Intelligence. We explain why businesses are moving to graph to solve complex data problems and then explain why existing BI solutions fall short when paired with graph technology. View a preview of what the future of graph-based BI looks like. This talk walks through the adoption of graph databases to solve complex business problems through the required evolution of business intelligence tools to support this new technology. The talk will review the benefits of graph database vs relational database for data science and businesses use cases, e.g. Customer 360, law enforcement - - We will show how the graph database is essentially an enhanced relational database where relationships are expressed directly as edges, rather than indirectly as joins. We examine how this structure gives rise to major benefits when dealing with very large datasets, and in looking for patterns buried in multi-party relationships. We will discuss and demonstrate some of the more sophisticated graph-based visualizations and algorithms that are now possible. ----------------------------- Speaker Bios ----------------------------- Clark Richey (https://www.linkedin.com/in/clark-richey-6b737) has over 20 years’ experience in architecting, designing, and implementing large scale systems, primarily for US Defense and Intelligence agencies. Prior to co-founding FactGem, where he currently works as the CTO, Clark was the Director of Public Sector Sales Engineering for MarkLogic. Clark has also taught computer science at the bachelor's and master's level at UMBC and Loyola University, respectively. Clark is a founding Java Champion and loves sharing his passion for computer science. Weidong Yang (https://www.linkedin.com/in/yangweidong) is the founder and CEO of Kineviz, a San Francisco-based data visualization company with the mission of solving difficult big data problem with interactive visual analytics. He received his Ph. D in Physics and Master in Computer Science. Prior to starting Kineviz, he conducted research on quantum dots as a postdoctoral fellow at UC, Berkeley, followed by a decade in the semiconductor industry as both product manager and researcher for advanced metrology tools. Weidong is also the founder and director of Kinetech Arts, a non-profit creative collective that bridges dance, science and interactive technologies. He has been credited with 10 US patents. Food will be kindly sponsored by our friends at Neo4j

  • Diversity in AI @ H2O World SF

    Hilton San Francisco Union Square

    H2O World is gathering Data Scientist from across the US and the World. To democratize AI we also need to be inclusive. H2O World has been working with various diversity groups like Black Girls Code, LatinX in AI, Black in AI, AI 4 All, SHPE and Teens Exploring Tech (TXT). This meetup is to network, discuss our efforts to democratize AI in our respective communities and discuss potential collaboration.

  • Diversity in AI @ H2O World SF

    Hilton San Francisco Union Square

    H2O World is gathering Data Scientist from across the US and the World. To democratize AI we also need to be inclusive. H2O World has been working with various diversity groups like Black Girls Code, LatinX in AI, Black in AI, AI 4 All, SHPE and Teens Exploring Tech (TXT). This meetup is to network, discuss our efforts to democratize AI in our respective communities and discuss potential collaboration.

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  • H2O World 2019 San Francisco

    Hilton San Francisco Union Square

    Hello Makers! We're headed back home to host our first H2O World San Francisco! Join the greatest minds in AI and data science for this 2-day interactive event packed with deep-dive technical sessions, talks on real-world business use cases and a hands-on training. You'll discover the strategies and insights you need to optimize and transform your business and prepare for the wave of AI. H2O World San Francisco is a must-attend event whether you're a newbie getting your toes wet, or an H2O power user. You'll get to network with industry trailblazers and connect with your peers who are shaping the future of AI and machine learning. Following is the agenda for the conference: February 4, 2019 This day will be a hands-on training of our groundbreaking products, H2O Driverless AI, H2O-3 and Sparkling Water. Join your fellow data scientists, developers and engineers in this technical deep-dive of H2O. February 5, 2019 The conference will feature talks and technical sessions from all walks of our community: Makers, Industry Leaders, Data Scientists, Kaggle Grandmasters, and machine learning enthusiasts alike. We have a number of panels to fill your data science appetite including Women in Data Science and Inclusion and Meet the Kaggle Grandmasters. The day culminates with a reception including our infamous H2O themed cocktails, DJ and a book signing. Space is limited so be sure to register early to save your seat at the AI education destination of the year. Register here: world.h2o.ai To get a discounted ticket, please use discount code MEETUP50 on our general admission tickets to get a discount! Note: RSVP'ing on this meetup page doesn't account for your ticket to H2O World 2019. Please visit the official website at world.h2o.ai and save a spot!

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  • Future-proof your Career: Expert Panel Discussion on Opportunities in AI

    Hello Makers! Join us this evening to discuss opportunities in AI! 6 - 6:30 PM - Doors open and pizza 6:30 - 7:30 PM - Panel discussioin 7:15 - 8:00 PM - Q&A and Networking We are excited to kick off the new year with an expert panel discussion in partnership with H20.ai that will answer all your burning questions on latest job trends and career opportunities in AI. The latest World Economic Forum (WEF) Future of Jobs report says, while new technologies can drive business growth, job creation and demand for specialized skills, they can also displace entire job categories when certain tasks become obsolete or automated. WEF analysis has found extensive evidence of accelerating demand for a variety of new specialist roles to latest emerging technologies: AI and Machine Learning Specialists, User Experience and Human-Machine Interaction Designers, Robotics Engineers and others. While, KPMG says the top 5 new jobs in AI are AI Architect, AI Product Manager, Data Scientist, AI Technology Software Engineer, and AI Ethicist. This changing landscape makes it critical for professionals to future-proof their skills to take advantage of these new opportunities in AI. So we have invited a group of brilliant AI professionals from Amazon, Intel and other leading global organizations to share their insights on: 1) New types of jobs, career paths and opportunities in AI 2) Skills you need to be successful in this new AI age 3) Useful tips on how to land your next opportunity in this space P.S. - Do remember to book your tickets to H2O World at world.h2o.ai.

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  • Model Deployment for Engineers

    Metis Data Science

    Hello Makers! Join us this evening to discuss how engineers can deploy machine learning models! Following is a brief agenda for the evening: 6 - 6:30 PM - Doors open and pizza 6:30 - 7:15 PM - Nicholas' Talk 7:15 - 7:45 PM - Q&A and Networking 7:45 - 8 PM - Contest for special prize! Deploying machine learning models can be a pain point for many engineering teams. There are multiple avenues for success for a particular project but there can also be roads to disaster. In this talk, I will discuss how to deploy Driverless AI pipelines. Topics will include the advantages and disadvantages for each deployment option - for example, why you might want to communicate to your scoring service over HTTP instead of using the language-level API. In addition, I will discuss general best practices that I have seen work and leave time to discuss your production questions - or new theories you now have as a result of the talk. About Nicholas: Nicholas Png is a Partnerships Software Engineer at H2O.ai. Prior to working at H2O, he worked as a Quality Assurance Software Engineer, developing software automation testing. Nicholas holds a degree in Mechanical Engineering, and has experience working with customers across multiple industries, identifying common problems, and designing robust, automated solutions.

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  • Introduction to Deep Learning, Keras, and TensorFlow

    Metis Data Science

    We'll be kicking off the New Year with an Introduction to Deep Learning, Keras, and TensorFlow with Oswald Campesato. Thank you Metis SF for hosting our meetup! Agenda: 6:00 - 6:30 PM: Doors open for networking and pizza 6:30 - 7:15 PM: Oswald's talk 7:15 - 7:45 PM: Speaker #2 - TBD 7:45 - 8:00 PM: Q&A Description: This fast-paced session starts with a simple yet complete neural network (no frameworks), followed by an overview of activation functions, cost functions, backpropagation, and then a quick dive into CNNs. Next, we'll create a neural network using Keras, followed by an introduction to TensorFlow and TensorBoard. For best results, familiarity with basic vectors and matrices, inner (aka "dot") products of vectors, and rudimentary Python is definitely helpful. If time permits, we'll look at the UAT, CLT, and the Fixed Point Theorem. (Bonus points if you know Zorn's Lemma, the Well-Ordering Theorem, and the Axiom of Choice.) Oswald's Bio: Oswald Campesato is an education junkie: a former Ph.D. Candidate in Mathematics (ABD), with multiple Master's and 2 Bachelor's degrees. In a previous career, he worked in South America, Italy, and the French Riviera, which enabled him to travel to 70 countries throughout the world. He has worked in American and Japanese corporations and start-ups, as C/C++ and Java developer to CTO. He works in the web and mobile space, conducts training sessions in Android, Java, Angular 2, and ReactJS, and he writes graphics code for fun. He's comfortable in four languages and aspires to become proficient in Japanese, ideally sometime in the next two decades. He enjoys collaborating with people who share his passion for learning the latest cool stuff, and he's currently working on his 15th book, which is about Angular 2. --- Don't forget to register for H2O World San Francisco on February 4-5, 2019. See the latest agenda and speakers here: world.h2o.ai

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