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Finding Clarity in the Automated Modeling Space
by Thomas Ott | December 12, 2018 H2O Driverless AI

There is an arms race happening in Data Science and Machine Learning space. It’s the race toward automation. Granted, the questions we as Data Scientists are asked to solve for will never be automated, but many of the routine tasks will be. What are these routine tasks? They range from data ingestion to feature generation. Then we have l...

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For Today’s BI Analyst - Accelerating your AI/ML efforts with Driverless AI
by Karthik Guruswamy | December 10, 2018 Data Science , H2O Driverless AI

Whether you are starting out as a novice data scientist or a veteran in AI and Machine Learning, modern tools can guide you in creating some of the best models from your data. Not to mention, ease of moving models to production.Also don’t forget the experienced BI Analysts in your organization, who wants to play with data science , only t...

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The Making of H2O Driverless AI - Automatic Machine Learning
by Arno Candel | December 05, 2018 Community , H2O Driverless AI , H2O World , H2O4GPU , Makers

It is my pleasure to share with you some never before exposed nuggets and insights from the making of H2O Driverless AI, our latest automatic machine learning product on our mission to democratize AI. This has been truly a team effort, and I couldn’t be more proud of our brilliant makers who continue to relentlessly create and innovate. T...

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Gratitude and thank you, makers!
by Sri Ambati | November 21, 2018 Community , Makers

Makers,Happy Thanksgiving – Hope you get to spend time with your loved ones this week.Thank them on our behalf, on your own, thank our neighbors, thank our teachers, thank our firemen, doctors, our farmers, our uber/lyft drivers, our engineers, our assistants, painters, news writers, bartenders, our chefs and a million others who play the...

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New features in H2O 3.22
by Erin LeDell, Michal Kurka | November 12, 2018 H2O Release

Xia Release (H2O 3.22)There’s a new major release of H2O and it’s packed with new features and fixes! Among the big new features in this release, we introduce Isolation Forest to our portfolio of machine learning algorithms and integrates the XGBoost algorithm into our AutoML framework. The release is named after Zhihong Xia .Isolation ...

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Top 5 things you should know about H2O World London
by H2O.ai Team | November 06, 2018 Community , Events , H2O World

We had a blast at H2O World London last week! With a record number of attendees on-site and through the live stream, it’s clear that our AI and machine learning conference was indeed a huge success and we strongly believe this achievement is a result of dedicated preparation and great love – for and from – our community and makers. So, fi...

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Anomaly Detection with Isolation Forests using H2O
by Martin Barus | November 06, 2018 Data Science , H2O-3

IntroductionAnomaly detection is a common data science problem where the goal is to identify odd or suspicious observations, events, or items in our data that might be indicative of some issues in our data collection process (such as broken sensors, typos in collected forms, etc.) or unexpected events like security breaches, server failu...

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Launching the Academic Program … OR ... What Made My First Four Weeks at H2O.ai so Special!

We just launched the H2O.ai Academic Program at our sold-out H2O World London. With nearly 1000 people in attendance, we received the first online sign-up forms submitted by professors and students alike. This program will massively democratize AI in academia, increasing the number of AI-skilled graduates – with both technical and busine...

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Welcome H2O.ai's Driverless AI Community!
by H2O.ai Team | October 30, 2018 Beginners , Community , H2O Driverless AI , H2O-3

I am very excited to announce the formation of the inaugural community for H2O Driverless AI users. The Driverless AI Community is open for anyone looking to engage with other users as well as experts from H2O.ai’s Driverless AI, Driverless AI is an award-winning automatic machine learning platform that does “AI to do AI” to solve re...

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How This AI Tool Breathes New Life Into Data Science

Ask any data scientist in your workplace. Any Data Science Supervised Learning ML/AI project will go through many steps and iterations before it can be put in production. Starting with the question of “Are we solving for a regression or classification problem?” Data Collection & Curation Are there Outliers? What is the Distribu...

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What does NVIDIA’s Rapids platform mean for the Data Science community?

Today NVIDIA announced the launch of the RAPIDS suite of software libraries to enables GPU acceleration for data science workflows and we’re excited to partner with NVIDIA to bring GPU accelerated open source technology for the machine learning and AI community. “Machine learning is transforming businesses and NVIDIA GPUs are speeding...

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Automatic Feature Engineering for Text Analytics - The Latest Addition to Our Kaggle Grandmasters' Recipes
by Jo-Fai Chow, Sudalai Rajkumar | September 12, 2018 Data Science , GPU , H2O Driverless AI , NLP

According to Kaggle’s ‘The State of Machine Learning and Data Science ’ survey , text data is the second most used data type at work for data scientists. There are a lot of interesting text analytics applications like sentiment prediction, product categorization, document classification and so on. In the latest version (1.3) of our Driver...

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Key Takeaways from the Forrester Notebook Wave
by Vinod Iyengar | September 07, 2018

The Forrester Wave: Notebook-Based Predictive Analytics and Machine Learning Solutions, Q3 2018 is out, and H2O.ai is a Strong Performer! The report looks at machine learning platforms centered on R and Python languages using notebooks like Jupyter and Zeppelin. Vendors are evaluated along three dimensions including market presence, curre...

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H2O for Inexperienced Users
by H2O.ai Team | August 24, 2018 Beginners , Data Science , H2O-3 , Machine Learning

Some background: I am a rising senior in highschool, and the summer of 2018, I interned at H2O.ai. With no ML experience beyond Andrew Ng’s Introduction to Machine Learning course on Coursera and a couple of his deep learning courses, I initially found myself slightly overwhelmed by the variety of new algorithms H2O has to offer in both ...

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Interpretability: The missing link between machine learning, healthcare, and the FDA?

Recent advances enable practitioners to break open machine learning’s “black box”.From machine learning algorithms guiding analytical tests in drug manufacture, to predictive models recommending courses of treatment, to sophisticated software that can read images better than doctors, machine learning has promised a new world of healthcar...

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The different flavors of AutoML
by Erin LeDell | August 15, 2018 AutoML , Data Science , H2O Driverless AI , H2O-3

In recent years, the demand for machine learning experts has outpaced the supply, despite the surge of people entering the field. To address this gap, there have been big strides in the development of user-friendly machine learning software (e.g. H2O , scikit-learn , keras ). Although these tools have made it easy to train and evaluate ma...

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H2O’s AutoML in Spark
by Jakub Hava | July 23, 2018 AutoML , Sparkling Water , Technical , Tutorials

This blog post demonstrates how H2O’s powerful automatic machine learning can be used together with the Spark in Sparkling Water.We show the benefits of Spark & H2O integration, use Spark for data munging tasks and H2O for the modelling phase, where all these steps are wrapped inside a Spark Pipeline. The integration between Spark and...

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H2O-3 on FfDL: Bringing deep learning and machine learning closer together
by Vinod Iyengar | June 25, 2018 Community , Deep Learning , H2O-3 , Technical

This post originally appeared in the IBM Developer blog here. This post is co-authored by Animesh Singh, Nicholas Png, Tommy Li, and Vinod Iyengar. Deep learning frameworks like TensorFlow, PyTorch, Caffe, MXNet, and Chainer have reduced the effort and skills needed to train and use deep learning models. But for AI developers and data ...

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How to Frame Your Business Problem for Automatic Machine Learning

Over the last several years, machine learning has become an integral part of many organizations’ decision-making at various levels. With not enough data scientists to fill the increasing demand for data-driven business processes, H2O.ai has developed a product called Driverless AI that automates several time consuming aspects of a typica...

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Time is Money! Automate Your Time-Series Forecasts with Driverless AI
by Jo-Fai Chow | June 12, 2018 H2O Driverless AI

Time-series forecasting is one of the most common and important tasks in business analytics. There are many real-world applications like sales, weather, stock market, energy demand, just to name a few. We strongly believe that automation can help our users deliver business value in a timely manner. Therefore, once again we translated our ...

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H2O.ai and IBM build a Strategic Partnership to bring AI innovation to the market together
by Sri Ambati | June 07, 2018

Excited to announce our strategic partnership with IBM that allows them to resell and take to market H2O Driverless AI to businesses worldwide. This partnership makes AI economical – faster, cheaper and easier to do experiments. H2O Driverless AI and IBM POWER9 GPU Systems are bringing together the best of breed AI innovation. We have b...

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AI in Healthcare - Redefining Patient & Physician Experiences
by H2O.ai Team | May 14, 2018 Community , Data Science , Deep Learning

Register for the Meetup Here Patients, physicians, nurses, health administrators and policymakers are beneficiaries of the rapid transformations in health and life sciences. These transformations are being driven by new discoveries (etiology, therapies, and drugs/implants), market reconfiguration and consolidation, a movement to value-bas...

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From Kaggle Grand Masters’ Recipes to Production Ready in a Few Clicks
by Jo-Fai Chow | May 09, 2018 H2O Driverless AI , Tutorials

Introducing Accelerated Automatic Pipelines in H2O Driverless AIAt H2O, we work really hard to make machine learning fast, accurate, and accessible to everyone. With H2O Driverless AI, users can leverage years of world-class, Kaggle Grand Masters experience and our GPU-accelerated algorithms (H2O4GPU ) to produce top quality predictive ...

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H2O World coming to NYC
by H2O.ai Team | May 08, 2018 Community

Whether you’re just starting out learning how machine learning and H2O.ai can supercharge your business or a veteran looking for more, we want to invite you to join some of greatest minds in the field to learn how AI and H2O.ai can transform your business. Our flagship event, H2O World is back and it’s going to be bigger than ever! We’re ...

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Democratize care with AI — AI to do AI for Healthcare
by H2O.ai Team | April 23, 2018 Customers , Healthcare , Machine Learning

Very excited to have Prashant Natarajan (@natarpr) join us along with Sanjay Joshi on our vision to change the world of healthcare with AI. Health is wealth. And one worth saving the most. They bring invaluable domain knowledge and context to our cause. As one of our customers would like to say, Healthcare should be optimized for health...

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Sparkling Water 2.3.0 is now available!
by H2O.ai Team | April 12, 2018 Sparkling Water

Hi Makers! We are happy to announce that Sparkling Water now fully supports Spark 2.3 and is available from our download page . If you are using an older version of Spark, that’s no problem. Even though we suggest upgrading to the latest version possible, we keep the Sparkling Water releases for Spark 2.2 and 2.1 up-to-date with the lates...

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H2O + Kubeflow/Kubernetes How-To
by H2O.ai Team | March 29, 2018 H2O-3

Today, we are introducing a walkthrough on how to deploy H2O 3 on Kubeflow. Kubeflow is an open source project led by Google that sits on top of the Kubernetes engine. It is designed to alleviate some of the more tedious tasks associated with machine learning. Kubeflow helps orchestrate deployment of apps through the full cycle of devel...

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Makers in Action: Community, Partners and Team Members at #GTC18
by H2O.ai Team | March 28, 2018 Events

NVIDIA’s GPU Technology Conference (GTC) has been incredible! Folks from all over the world are exploring the latest breakthroughs in self-driving cars, smart cities, healthcare, high performance computing, virtual reality, and more, all propelled by the AI movement. If you’re attending GTC and would like to see our solutions in action (r...

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H2O4GPU now available in R
by H2O.ai Team | March 27, 2018 GPU , R

In September, H2O.ai released a new open source software project for GPU machine learning called H2O4GPU . The initial release (blog post here ) included a Python module with a scikit-learn compatible API, which allows it to be used as a drop-in replacement for scikit-learn with support for GPUs on selected (and ever-growing) algorithms. ...

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Come meet the Makers!
by H2O.ai Team | March 26, 2018 Data Science , Events , H2O Driverless AI , H2O4GPU

NVIDIA’s GPU Technology Conference (GTC) Silicon Valley, March 26-29th is the premier AI and deep learning event, providing you with training, insights, and direct access to the industry’s best and brightest. It’s where you will see the latest breakthroughs in self-driving cars, smart cities, healthcare, high-performance computing, virtu...

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How Driverless AI Prevents Overfitting and Leakage
by H2O.ai Team | March 23, 2018 H2O Driverless AI

By Marios Michailidis , Competitive Data Scientist, H2O.ai In this post, I’ll provide an overview of overfitting, k-fold cross-validation, and leakage. I’ll also explain how Driverless AI avoids overfitting and leakage.An Introduction to OverfittingA common pitfall that causes machine learning models to fail when tested in a real-world e...

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Sparkling Water 2.2.10 is now available!
by H2O.ai Team | March 22, 2018 AutoML , Sparkling Water

Hi Makers! There are several new features in the latest Sparkling Water. The major new addition is that we now publish Sparkling Water documentation as a website which is available here . This link is for Spark 2.2. We have also documented and fixed a few issues with LDAP on Sparkling Water. Exact steps are provided in the documentation...

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Congratulations - H2O is a leader in the Gartner Magic Quadrant for Data Science and Machine Learning Platforms
by H2O.ai Team | February 25, 2018 Community , Customers , Gartner , H2O-3

Congratulations – Thanks to the support of our customer community over the past years, H2O.ai is a leader and one with the most completeness of vision in Gartner Magic Quadrant for Data Science and Machine Learning Platforms. It is an ecosystem we dedicated a good part of this decade to open up and spring. This is testimony to the incr...

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New features in H2O 3.18
by H2O.ai Team | February 22, 2018 AutoML , Ensembles , H2O Release , XGBoost

Wolpert Release (H2O 3.18)There’s a new major release of H2O and it’s packed with new features and fixes! We named this release after David Wolpert , who is famous for inventing Stacking (aka Stacked Ensembles ). Stacking is a central component in H2O AutoML , so we’re very grateful for his contributions to machine learning! He is also fa...

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Developing and Operationalizing H2O.ai Models with Azure
by H2O.ai Team | January 24, 2018 Machine Learning

This post originally appeared here. It was authored by Daisy Deng, Software Engineer, and Abhinav Mithal, Senior Engineering Manager, at Microsoft. The focus on machine learning and artificial intelligence has soared over the past few years, even as fast, scalable and reliable ML and AI solutions are increasingly viewed as being vital to...

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