• Webinar: Using H2O Driverless AI for Cybersecurity

    *THIS IS A VIRTUAL EVENT* Registration Please follow this link to reserve your seat: https://www.h2o.ai/webinars/?commid=374408 Description: It is well-known that the Internet is the going to be the next battleground for everything to come. From misunderstandings, minor skirmishes, to fully-enabled state actors attacking governments. They are all positioned well to take advantage of: 1. The Cloak of the Internet 2. Remote attack locations 3. Asymmetry in impact 4. And an immense dependency of companies, people, governments, and every organization to be present on the internet. With this much at stake, the amount of resources that are poured into maintaining a secure network is remarkably low, and the job done by the people is nothing short of amazing. Unfortunately, this is limited in scale. And therefore, you need automated models. Automated-Machine-Learnt models do a tremendously quick and accurate job of detecting malicious behavior must faster, thereby averting any security violations. In this example, we will take datasets that should be vulnerable to potential attacks, and show how Driverless AI and the feature engineering capability can solve this problem. Presenter: Ashrith Barthur, Chief Security Scientist, H2O.ai

  • Accelerate Machine Learning Deployment with H2O Driverless AI on AWS

    Join this half-day workshop for a hands-on experience of Driverless AI on AWS. ***** Please RSVP on this link to save your spot: https://www.eventbrite.com/e/accelerate-machine-learning-deployment-with-h2o-driverless-ai-on-aws-tickets-70535287945 ***** Your RSVP on meetup.com will not be counted towards your seat. About this Event In every company, thousands of AI models will be required to automate and enhance workflows and accelerate the innovation of new digital products. Existing machine learning systems take months to develop and deploy a single model. Reducing the time that it takes to develop accurate, production-ready models is critical to solving a large number of business challenges with AI. In this workshop, we’ll cover how Driverless AI automates some of the most difficult data science and machine learning workflows such as feature engineering, model validation, model tuning, model selection, and model deployment. You’ll learn how to deploy production-ready models as an AWS Lambda function or using Amazon Sagemaker. Note: Please bring your laptop and power cords to participate in the training. ------------------------------------------------------------------------------------------------------ Join this half-day workshop for a hands-on experience of Driverless AI on AWS. In this session you will learn more about: How to ingest and visualize your dataset Feature engineering to obtain the most accurate results from algorithms Robust interpretability of machine learning models to explain modeling results Scoring pipelines and new ultra-low latency automatic scoring pipelines Deploying models as an Amazon Lambda Function or using Amazon Sagemaker platform ------------------------------------------------------------------------------------------------------ Agenda at a glance: 8:30-9:00 Registration, Breakfast & Networking 9:00-9:30 Introduction to H2O Driverless AI 9:30-10:00 Customer Stories and Use Cases 10:00-10:45 Interactive Demo: Automatic feature engineering 10:45-11:30 Interactive Demo: Machine Learning Interpretability 11:30-12:00 Interactive Demo: Deploying scoring pipelines using AWS Lambda and Sagemaker 12:00-12:15 Q&A Space is limited for this event. Sign up today to reserve your spot! ------------------------------------------------------------------------------------------------------ Speaker's bio: Michelle is a Customer Solutions Engineer & Data Scientist for H2O.ai. Prior to H2O she worked as a Senior Data Science Consultant for Teradata, focused on leading analytics projects to solve cross-industry business problems. Her background is in pure math and computer science and she is passionate about applying these skills to answer real-world questions. When not coding or thinking of analytics, Michelle can be found hanging out with her dog or playing the ukulele.

    2
  • Webinar: What's New in H2O Driverless AI

    Live Webinar

    *THIS IS A VIRTUAL EVENT* Registration Please follow this link to reserve your seat: https://www.h2o.ai/webinars/?commid=365344 Description H2O Driverless AI employs the techniques of expert data scientists in an easy to use application that helps scale your data science efforts. Driverless AI empowers data scientists to work on projects faster using automation and state-of-the-art computing power from GPUs to accomplish tasks in minutes that used to take months. In this webinar we'll highlight what's new in Driverless AI. Presenter: Arno Candel, CTO at H2O.ai

  • Explainable AI with H2O Driverless AI’s Machine Learning Interpretability Module

    Hello Seattle Makers! Join us this evening to hear from our own Michelle Tanco about Explainable AI with H2O Driverless AI’s Machine Learning Interpretability Module. Explainable AI is in the news, and for good reason. Financial services companies have cited the ability to explain AI-based decisions as one of the critical roadblocks to further adoption of AI for their industry. Transparency, accountability, and trustworthiness of data-driven decision support systems based on AI and machine learning are serious regulatory mandates in banking, insurance, healthcare, and other industries. From pertinent regulations to increasing customer trust, data scientists and business decision-makers must show AI-based decisions can be explained. H2O Driverless AI does explainable AI today with its machine learning interpretability (MLI) module. This capability in H2O Driverless AI employs a unique combination of techniques and methodologies to explain the results of both Driverless AI models and external models. Following is a brief agenda for the evening: 6:00 - 6:30 PM: Doors open for networking and pizza 6:30 - 7:15 PM: Michelle's talk 7:15 - 7:30 PM: Q&A 7:30 PM - 8:00: Networking Michelle's Bio: Michelle is a Customer Solutions Engineer & Data Scientist for H2O.ai. Prior to H2O she worked as a Senior Data Science Consultant for Teradata, focused on leading analytics projects to solve cross-industry business problems. Her background is in pure math and computer science and she is passionate about applying these skills to answer real-world questions. When not coding or thinking of analytics, Michelle can be found hanging out with her dog or playing the ukulele.

  • Live From New York City, it's H2O.ai!

    Live Webcast

    Hello Makers! H2O.ai will be announcing exciting news from New York City on Tuesday, August 20, 2019 and we will love for you to be a part of this celebration. Save your spot at the live webcast by visiting this link: https://www.h2o.ai/livefromnyc/ Stay tuned for more, see you shortly!

  • Webinar: How to Make a Recipe with H2O Driverless AI

    *THIS IS A VIRTUAL EVENT* Registration Please follow this link to reserve your seat: https://www.h2o.ai/webinars/?commid=364997 Description H2O Driverless AI employs the techniques of expert data scientists in an easy to use application that helps scale your data science efforts. Driverless AI empowers data scientists to work on projects faster using automation and state-of-the-art computing power from GPUs to accomplish tasks in minutes that used to take months. We're excited to add the ability for users, partners and customers to extend the platform with Bring-Your-Own-Recipe. 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. In this webinar we'll demonstrate how make a recipe with Driverless AI. Presenter: Michelle Tanco, H2O.ai

  • 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

  • Intro to Deep Learning NLP with PyTorch @ Microsoft

    Needs a location

    Hi Seattle Makers! - This is meetup is co-promoted with organizers from the Seattle Artificial Intelligence Workshops meetup. Please see the information below. Intro to Deep Learning NLP with PyTorch @ Microsoft RSVP HERE: https://www.eventbrite.com/e/intro-to-deep-learning-nlp-with-pytorch-tickets-62546873382 Deep Learning is the latest rising trend in Machine Learning (ML), and PyTorch is one of the top three deep learning frameworks originally developed by Facebook with Python as a first-class citizen. One of the biggest areas in ML that has been advanced by Deep Learning is Natural Language Processing (NLP). This event is sponsored by Microsoft. The organizers from Redmond and the Bay Area have given several workshops in the past at Google and TechCode accelerator on TensorFlow and Scikit-Learn. Prerequisites: Laptop Power cable Photo ID (for registration) Schedule (tentative) 9-10AM Registration, breakfast, setup 10AM-10:30PM Introduction 10:30AM-12PM talks 12-1PM Lunch 1-4PM Talks RSVP HERE: https://www.eventbrite.com/e/intro-to-deep-learning-nlp-with-pytorch-tickets-62546873382

  • 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.

  • Scalable Automatic Machine Learning with H2O

    Hello Makers, Join us this evening to learn about scalable automatic machine learning with H2O. Following is a brief agenda for the evening: 6:30 - 7:00 PM: Doors open & Networking 7:00 - 8:00 PM: Erin's Talk 8:00 - 8:15 PM: Q&A Description: In this presentation, Erin LeDell (Chief Machine Learning Scientist, H2O.ai), will provide a history and overview of the field of “Automatic Machine Learning” (AutoML), followed by a detailed look inside H2O’s open source AutoML algorithm. H2O AutoML provides an easy-to-use interface which automates data pre-processing, training and tuning a large selection of candidate models (including multiple stacked ensemble models for superior model performance). The result of the AutoML run is a “leaderboard” of H2O models which can be easily exported for use in production. AutoML is available in all H2O interfaces (R, Python, Scala, web GUI) and due to the distributed nature of the H2O platform, can scale to very large datasets. The presentation will end with a demo of H2O AutoML in R and Python, including a handful of code examples to get you started using automatic machine learning on your own projects. Speaker's Bio: Erin is the Chief Machine Learning Scientist at H2O.ai. Erin has a Ph.D. in Biostatistics with a Designated Emphasis in Computational Science and Engineering from University of California, Berkeley. Her research focuses on automatic machine learning, ensemble machine learning and statistical computing. She also holds a B.S. and M.A. in Mathematics. Before joining H2O.ai, she was the Principal Data Scientist at Wise.io (acquired by GE Digital in 2016) and Marvin Mobile Security (acquired by Veracode in 2012), and the founder of DataScientific, Inc.

    2