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H2O Release 3.28 (Yu)
by Michal Kurka | December 20, 2019 H2O Release

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’ve introduced support for Hierarchical GLM, added an option to parallelize Grid Search, upgraded XGBoost with newly added features, and improved our AutoML framework. The release is named after Bin Yu .Hierarchi...

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Why you should care about debugging machine learning models
by H2O.ai Team | December 12, 2019 Explainable AI , Machine Learning

This blog post was originally published here. Authors: Patrick Hall and Andrew Burt For all the excitement about machine learning (ML), there are serious impediments to its widespread adoption. Not least is the broadening realization that ML models can fail. And that’s why model debugging, the art and science of understanding and fixing p...

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Interview with Arno Candel | AutoML | Physics | CTDS.Show
by Sanyam Bhutani | December 12, 2019 Community , Company , Data Science

In this episode, Sanyam Bhutani interviews Dr. Arno Candel: CTO at H2O.ai They talk about Arno’s journey into the field with amazing comments and insights by Arno applicable to the field. They talk all about Arno’s journey and ML, Automated Machine Learning Broadly speaking. Arno’s journey from Physics to Software Engineering to Machine L...

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How to Effectively Employ an AI Strategy in your Business
by Parul Pandey | December 11, 2019 Beginners , Business , Machine Learning

Artificial Intelligence has evolved from being a buzz word to a reality today. Companies with expertise in machine learning systems are looking to graduate to Artificial Intelligence-based technologies. The enterprises that do not yet have a machine learning culture are trying to devise a strategy to put one in place. Amidst t...

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Scalable AutoML in H2O
by Sanyam Bhutani | November 27, 2019 AutoML , H2O World , Machine Learning , Technical

Note: I’m grateful to Dr. Erin LeDell for the suggestions, corrections with the writeup. All of the images used here are from the talks’ slides. Erin Ledell’s talk was aimed at AutoML : Automated Machine Learning , broadly speaking, followed by an overview of H2O’s Open Source Project and the library. H2O AutoML provides an easy-to-use ...

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Meet Yauhen Babakhin: The first and the only Kaggle Grandmaster from Belarus
by Parul Pandey | November 22, 2019 Makers

There is more to competitive Data Science than simply applying algorithms to get the best possible model. The main takeaway from participating in these competitions is that they provide an excellent opportunity for learning and skill-building. The learnings can then be utilized in one’s academic or professional life. Kaggle is one of th...

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Climbing the AI and ML Maturity Model Curve
by Karthik Guruswamy | November 19, 2019 Data Science , Machine Learning , Technical

AI/ML Maturity Model Curve/StepsAI/ML Maturity models are published and updated periodically by a lot of vendors. The end goal is almost always about effecting transformation and automate processes in a short period and making AI the DNA/core of the business.One of the biggest challenges for businesses today is to clearly define what succ...

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How to write a Transformer Recipe for Driverless AI
by Ashrith Barthur | November 18, 2019 H2O Driverless AI , Machine Learning , Recipes

What is a transformer recipe? A transformer (or feature) recipe is a collection of programmatic steps, the same steps that a data scientist would write a code to build a column transformation. The recipe makes it possible to engineer the transformer in training and in production. The transformer recipe, and recipes, in general, provide a...

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Novel Ways To Use Driverless AI

I am biased when I write that Driverless AI is amazing, but what’s more amazing is how I see customers using it. As a Sales Engineer, my job has been to help our customers and prospects use our flagship product. In return, they give us valuable feedback and talk about how they used it. Feedback is gold to us. Driverless AI has evolved in...

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Image Tasks on H2O Driverless AI
by Sanyam Bhutani | November 12, 2019 H2O Driverless AI , H2O World , Makers

I’d like to thank Grandmaster Yauhen Babakhin for reviewing the drafts and the very useful corrections & suggestions. Link to the video. IntroductionIn this talk Kaggle GrandMaster and Data Scientist at H2O.ai: Yauhen Babakhin shows us a few prototype demos of how DriverlessAI’s upcoming release will work with Image Data and the relat...

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Accelerate Machine Learning workflows with H2O.ai Driverless AI on Red Hat OpenShift, Enterprise Kubernetes Platform
by Nicholas Png | November 12, 2019 H2O Driverless AI , Kubernetes

Organizations globally are operationalizing containers and Kubernetes to accelerate Machine Learning lifecycles as these technologies provide data scientists and software developers with much needed agility, flexibility, portability, and scalability to train, test, and deploy ML models in production. Red Hat OpenShift is the industry’s mo...

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Importing, Inspecting, and Scoring With MOJO Models Inside H2O
by H2O.ai Team | November 08, 2019 H2O-3 , Technical

Machine-learning models created with H2O may be exported in two basic ways: Binary format, Model Object, Optimized (MOJO). An H2 O model can be saved in a binary format, which is tied to the very specific version of H2 O it has been created with. There are multiple reasons for such a restriction. One of the important reasons is that...

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Natural Language Processing in H2O’s Driverless AI
by Sanyam Bhutani | November 06, 2019 Community , H2O Driverless AI , H2O World , Makers , NLP

Note: I’d like to thank Grandmaster SRK for a lot of suggestions and corrections with the writeup.Note: All images used here are from the talk. Link to the slides Link to the video Note 2: All of the discussion here is related to NLP. DriverlessAI also supports other domains that are covered in other talks and posts (releasing soon). Driv...

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Highlights of H2O World New York 2019
by H2O.ai Team | November 02, 2019 Community , H2O World , Makers

H2O World New York happened a few days ago and we are still in awe of the conference. It is rewarding to see such a strong community and recognized industry professionals making meaningful connections and learning with each other. We are grateful for having so many makers and customers joining us – in person and via live stream – for a fu...

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Takeaways from the World’s largest Kaggle Grandmaster Panel

Disclaimer: We were made aware by Kaggle of adversarial actions by one of the members of this panel. This panelist is no longer a Kaggle Grandmaster and no longer affiliated with H2O.ai as of January 10th, 2020. Personally, I’m a firm believer and fan of Kaggle and definitely look at it as the home of Data Science. ...

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A Full-Time ML Role, 1 Million Blog Views, 10k Podcast Downloads: A Community Taught ML Engineer
by Sanyam Bhutani | October 17, 2019 Data Science , Machine Learning Interpretability , Makers

Content originally posted in HackerNoon and Towards Data Science 15th of October, 2019 marks a special milestone, actually quite a few milestones. So I considered sharing it in the form a blog post, on a publication that has been home to all of my posts The online community has been too kind to me and these blog posts have been a method ...

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The Data Scientist who rules the "Data Science for Good" competitions on Kaggle
by Parul Pandey | October 17, 2019 Makers

In conversation with Shivam Bansal: A Data Scientist, a Kaggle Kernel’s Grandmaster, and three times winner of Kaggle’s Data Science for Good Competition. Communication is an art and a useful tool in the Data Science domain. Being able to communicate the insights is necessary so that others can take the required actions based on the resu...

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A Deep Dive into H2O’s AutoML
by Parul Pandey | October 16, 2019 AutoML , H2O-3 , Technical

The demand for machine learning systems has soared over the past few years. This is majorly due to the success of Machine Learning techniques in a wide range of applications. AutoML is fundamentally changing the face of ML-based solutions today by enabling people from diverse backgrounds to use machine learning models to address complex ...

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Make your own AI — Add Your Game to Auto-ML Models
by Karthik Guruswamy | October 15, 2019 AutoML , H2O Driverless AI , Machine Learning , Technical

When Features and Algorithms compete, your Business Use Case(s) wins! H2O Driverless AI is an Automatic Feature Engineering /Machine Learning platform to build AI/ML models on tabular data. Driverless AI can build supervised learning models for Time Series forecasts, Regression , Classification , etc. It supports a myriad of built-i...

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H2O World New York: The Countdown is On!
by H2O.ai Team | October 14, 2019 Community , Company , Events , H2O World , Makers

Every H2O World is magical. The preparation for the conference starts many months in advance and we put a lot of effort and love in every single detail to provide our beloved community with the best experience possible. Our upcoming H2O World New York on October 22 is the third edition I work on as part of the marketing team at H2O.ai. My...

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5 Key Takeaways On Overcoming Gender and Diversity Barriers
by H2O.ai Team | October 04, 2019

Overcoming gender and diversity barriers in the workplace is a challenge for many industries. Therefore, listening to women and discussing the topic is the first step towards finding out how to address gender bias and possible inequalities. Last month, H2O.ai organized a panel in New York: Breaking gender and diversity barriers in machi...

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Predicting Failures from Sensor Data using AI/ML — Part 2
by Karthik Guruswamy | September 27, 2019 H2O Driverless AI , Recipes , Technical

This is Part 2 of the blog post series and continuation of the original post, Predicting Failures from Sensor Data using AI/ML — Part 1 .Missing Values & Data ImbalanceOne of the things to note is that the hard-disk data set has a lot of missing values across its columns. Check out the Missing Data Heat Map on the training data set — ...

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H2O Driverless AI: The Workbench for Data Science

This blog was written by Rohan Gupta and originally published here. 1. IntroductionIn today’s world, being a Data Scientist is not limited to those without technical knowledge. While it is recommended and sometimes important to know a little bit of code, you can get by with just intuitive knowledge. Especially if you’re on H2O’s Driverle...

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H2O Driverless AI Acceleration with Intel DAAL
by Rafael Coss | September 25, 2019 Data Science , H2O Driverless AI , Machine Learning

This week at Strata NY 2019 we will be demoing a custom recipe that incorporates the Intel Data Analytics Acceleration Libraray (DAAL) algorithm into Driverless AI. This blog will provide an introduction to Intel DAAL and how the Make-Your-Own-Recipe capability extends H2O Driverless AI. If you are at Strata NY 2019, stop by the Intel bo...

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Custom recipes for Driverless AI: Prophet and pmdarima cases
by Marios Michailidis | September 24, 2019 H2O Driverless AI , Recipes , Technical

Last updated: 09/23/19 H2O Driverless AI provides a great new feature called “custom recipes”. These recipes are essentially custom snippets of code which can incorporate any machine learning algorithm , any scorer/metric and any feature transformer. A user can create custom recipes using python utilizing any external library or his/her o...

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From Academia to Kaggle and H2O.ai: How a Physicist found love in Data Science
by Parul Pandey | September 16, 2019 H2O Driverless AI , Machine Learning , Makers

Learning and taking inspirations from others is always helpful. It makes even more sense in the Data Science realm, which is continuously being bombarded with new courses, MOOCs, and recommendations with every passing day. Not only such a lot of choices become overwhelming but also perplexing at times. With this thought in mind, we bring...

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Regression Metrics' Guide
by Marios Michailidis | September 09, 2019

Introduction As part of my role within the automated machine learning space with H2O.AI and Driverless AI, I have seen that many times people struggle to find the right optimization metric for their data science problems. This process is even more challenging in regression problems where the errors are often not bounded like you norma...

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Series ‘D’emocratize
by Thomas Ott | September 07, 2019 Community , H2O Driverless AI , Makers

Last month was very emotional for me and I suspect it was the same for many of my fellow Makers at H2O.ai. The news broke that H2O.ai raised its Series D funding of $72.5 million led by Goldman Sachs and Ping An. While some of my friends were ecstatic for me, I felt like a big weight had been lifted off me. The best word to describe what ...

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Driverless AI can help you choose what you consume next
by Parul Pandey | September 06, 2019

Last updated: 09/06/19 Steve Jobs once said, “A lot of times, people don’t know what they want until you show it to them’. This makes sense, especially in this era of constant choice overload. Consumers today have access to a plethora of products just at the click of their mouse. These innumerable choices can sometimes turn out to be ...

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Startup Aims to Democratize AI
by Ingrid Burton | September 05, 2019 Community , Company , Events , Guest Posts , Makers

Adam Janofsky at the Wall Street Journal wrote a wonderful article about our company, and our eloquent and philosophical CEO and Founder, Sri Ambati. The makers at H2O.ai believe deeply in our mission to democratize AI for everyone, and we can see a future where every company can be an AI company. Read more below, and enjoy! Startup Aims ...

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Predicting Failures from Sensor Data using AI/ML— Part 1
by Karthik Guruswamy | August 26, 2019 H2O Driverless AI , Machine Learning , Technical

Last updated: 08/26/19 Whether it’s healthcare, manufacturing or anything that we depend on either personal or in business, Prevention of a problem is always known to be better than cure! Classic prevention techniques involve time-based checks to see how things are progressing, positively or negatively. Time-based chec...

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New Innovations in Driverless AI

What’s new in Driverless AIWe’re super excited to announce the latest release of H2O Driverless AI . This is a major release with a ton of new features and functionality. Let’s quickly dig into all of that: Make Your Own AI with Recipes for Every Use Case: In the last year, Driverless AI introduced time-series and NLP recipes to meet the...

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Interns Gonna Make
by H2O.ai Team | August 16, 2019 Community

Blog post by Megan Chan When I first walked through the front doors of the H2O.ai Mountain View office, I have to admit, thoughts of robots, cyborgs, and Arnold Schwarzenegger as The Terminator were in the back of my mind. However, my initial preconceived notions were quickly put to rest.I am a third-year college intern studying Psycholog...

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A Maker Data Scientist’s journey: from Sudoku to Kaggle
by Parul Pandey | August 16, 2019 H2O Driverless AI , Machine Learning , Makers

If you put enough smart people together in one space, good things happen. Erik Hersman One of the perks of being a part of H2O.ai is that you get to work with some of the brightest minds on the planet. Here you get to closely engage with people who have a great deal of experience, as well as expertise. One such set of specialists here ar...

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My Summer Internship at H2O.ai
by Priya Jain | August 10, 2019 Community

I can’t believe the summer is nearing an end. What an amazing experience I have had at H2O.ai. As I reflect back, I am so fortunate to have learned so much, formed meaningful relationships, developed people skills and applied my creativity. The whole team has been so encouraging, supportive, and inviting throughout my internship, makin...

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Detecting Sarcasm is difficult, but AI may have an answer
by Parul Pandey | August 05, 2019 H2O Driverless AI , NLP , Recipes , Technical , Tutorials

Recently, while shopping for a laptop bag, I stumbled upon a pretty amusing customer review: “This is the best laptop bag ever. It is so good that within two months of use, it is worthy of being used as a grocery bag.” The innate sarcasm in the review is evident as the user isn’t happy with the quality of the bag. However, as the sentence...

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Mitigating Bias in AI/ML Models with Disparate Impact Analysis

Everyone understands that the biggest plus of using AI/ML models is a better automation of day-to-day business decisions, personalized customer service, enhanced user experience, waste elimination, better ROI, etc. The common question that comes up often though is — How can we be sure that the AI/ML decisions are free from bias/discrimina...

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H2O Release 3.26 (Yau)
by Michal Kurka | July 30, 2019 H2O Release

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’ve introduced the ability to define a Custom Loss Function in our GBM implementation, and we’ve extended the portfolio of our machine learning algorithms with the implementation of the SVM algorithm. The release...

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A Driverless Approach to Make Forecasting Easy — Part 1
by Karthik Guruswamy | July 25, 2019 H2O Driverless AI

You are from the supply chain department or in a role in charge of creating future estimates on Product Sales, Patient admission, Retail Store Staffing, Energy use, Ticket sales, etc., based on historical data. A common problem is to forecast numbers one week, 4 weeks, 6 months or 1–5 year, etc., in future — basically short term &a...

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Custom Machine Learning Recipes: The ingredients for success

Last updated: 07/23/19Machine learning is akin to cooking in several ways. A perfect dish originates from a tried-and-tested recipe, has the right combination of ingredients, and is baked at just the right temperature. Successful AI solutions work on the same principle. One needs fresh and right quality ingredients in the form of data, ...

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AI for Smarter Manufacturing
by Vinod Iyengar | July 19, 2019 H2O Driverless AI , Manufacturing , Solutions

Code 3Manufacturing is a centuries old industry and has seen significant changes dating back to the first Industrial Revolution in the late 18th century. The use of conveyor belt assembly lines to replace assembly workers, newer precision robot technologies to further reduce manufacturing time, advances in ERP, historian databases, stora...

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Leads to Leases

There is such a large amount of unstructured data being produced by companies. I personally find it so interesting that there is so much meaning and hidden value in text, audio, and visual content. Until recently, much of this data would go unused. However, since the rise of machine learning and artificial intelligence, it became possibl...

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Getting started with H2O using Flow
by Parul Pandey | July 16, 2019 Flow , H2O-3 , Technical

This blog was originally published on towardsdatascience: https://towardsdatascience.com/getting-started-with-h2o-using-flow-b560b5d969b8A look into H2O’s open-source UI for combining code execution, text, plots, and rich media in a single document. Data collection is easy. Decision making is hard. Today, we have access to a humungous...

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ArmadaHealth Uses AI to Match Patients with Specialists to Improve Health Outcomes
by Priya Jain | July 09, 2019 Customers , Data Science , Healthcare

As an intern for H2O.ai, I am amazed to see how instrumental AI has been in transforming people’s lives for the better. Especially in healthcare, AI is bringing increased efficiency, ease, and helping people lead healthier lives. In this blog, I learned about how AI is helping potential patients find the right specialist for their needs a...

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Toward AutoML for Regulated Industry with H2O Driverless AI

Predictive models in financial services must comply with a complex regime of regulations including the Equal Credit Opportunity Act (ECOA), the Fair Credit Reporting Act (FCRA), and the Federal Reserve’s S.R. 11-7 Guidance on Model Risk Management. Among many other requirements, these and other applicable regulations stipulate predictive ...

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Underwrite.ai Transforms Credit Risk Decision-Making Using AI

Determining credit has been done by traditional techniques for decades. The challenge with traditional credit underwriting is that it doesn’t take into account all of the various aspects or features of an individual’s credit ability. Underwrite.ai, a new credit startup, saw this as an opportunity to apply machine learning and AI to impro...

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The Reproductive Science Center of SF Bay Area uses AI to Treat Infertility

Having your own baby may be a dream that many people have but some cannot realize until they seek specialized help. The Reproductive Science Center of SF Bay Area is one of the pioneer organizations conducting in-vitro fertilization. They strive to produce healthy babies for their patients. However, every patient has their own set of obst...

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Machine Learning on VMware: Training a Model with H2O.ai Tools, Inference using a REST Server and Kubernetes
by Vinod Iyengar | June 10, 2019 Community

This blog was originally posted by Justin Murray of VMware and can be accessed here. In this article, we explore the tools and process for (1) training a machine learning model on a given dataset using the H2O Driverless AI (DAI) tool, and (2) deploying a trained model, as part of a scoring pipeline, to a REST server for use by busi...

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An Overview of Python’s Datatable package

This blog originally appeared on Towardsdatascience.com “There were 5 Exabytes of information created between the dawn of civilization through 2003, but that much information is now created every 2 days”: Eric Schmidt If you are an R user, chances are that you have already been using the data.ta...

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Building an Interpretable & Deployable Propensity AI/ML Model in 7 Steps…

To start with, you may have a tabular data set with a combination of: Dates/Timestamps Categorical Values Text strings Numeric Values A business sponsor wants to build a Propensity to Buy model from historical data.How many Steps does it take? Let’s find out. We are going to use H2O’s Driverless AI instance with 1 GPU (optional...

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Forrester Research recognizes H2O.ai as a leader in the New Automatic Machine Learning Wave
by Rafael Coss | May 28, 2019 Community , Customers , H2O Driverless AI

Today, The Forrester New Wave™ : Automation-Focused Machine Learning Solutions, Q2 2019 was published by Forrester Research. We are thrilled that this leading analyst firm recognized us as a clear leader in their Automatic Machine Learning evaluation. We could not be prouder of our unwavering strategy and hard work that we believe is prop...

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H2O.ai Automatic Machine Learning on Red Hat OpenShift Container Platform Delivers Data Science Ease and Flexibility at Scale
by Vinod Iyengar | May 14, 2019 Cloud , Data Science , Demos , H2O Driverless AI

Last week at Red Hat Summit in Boston, Sri Ambati, CEO and Founder, demonstrated how to use our award-winning automatic machine learning platform, H2O Driverless AI , on Red Hat OpenShift Container Platform. You can watch the replay here .What we showed not only helps data scientists achieve results, it also enables them to scale their ...

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6 Tips to Having it All
by Ingrid Burton | May 12, 2019 Community , Events

I posted this blog on Medium two years ago, thought I’d share a slight rework of it with all the Mothers and Makers out there again.It’s Mother’s Day, and today is when I count my blessings. I am the mother of a wonderful blended family. I have four children of my own, and three stepchildren. Do the math… that’s 7! They are all great you...

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AI/ML Projects — Don’t get stymied in the last mile

Data Scientists build AI/ML models from data, and then deploy it to production – in addition to a plethora of tasks around data insights, data cleansing etc., Part of the Data Scientist job description/requirement is making models available for transparency, auditability as well as explainability for both regulators as well as internal bu...

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Hortifrut uses AI to Determine the Freshness of Blueberries

Who doesn’t love sweet, delicious blueberries?Providing a steady supply of beautiful, tasty berries to the market is no small effort and Hortifrut, based in Chile, has been growing and distributing berries for the last 30 years. Today, they are using AI to provide fresh berries to the world everyday.Hortifrut, the largest global producer ...

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Can Your Machine Learning Model Be Hacked?!

I recently published a longer piece on security vulnerabilities and potential defenses for machine learning models. Here’s a synopsis.IntroductionToday it seems like there are about five major varieties of attacks against machine learning (ML) models and some general concerns and solutions of which to be aware. I’ll address them one-by-o...

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H2O Driverless AI Updates
by Venkatesh Yadav | April 25, 2019 H2O Driverless AI , Product Updates

We are excited to announce the new release of H2O Driverless AI with lots of improved features.Below are some of the exciting new features we have added:Version 1.6.1 LTS (April 18, 2019) – Available here Several improvements for MLI (partial dependence plots, Shapley values) Improved documentation for model deployment, time-series ...

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H2O World Explainable Machine Learning Discussions Recap

Earlier this year, in the lead up to and during H2O World, I was lucky enough to moderate discussions around applications of explainable machine learning (ML) with industry-leading practitioners and thinkers. This post contains links to these discussions, written answers and pertinent resources for some of the most common questions asked ...

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H2O-3, Sparkling Water and Enterprise Steam Updates
by Venkatesh Yadav | April 10, 2019 Community , Data Science , H2O Release , Technical

We are excited to announce the new release of H2O Core, Sparkling Water and Enterprise Steam.Below are some of the new features we have added:H2O-3 Yates (3.24.0.1) – 3/31/2019Download at: http://h2o-release.s3.amazonaws.com/h2o/rel-yates/1/index.html Bug [PUBDEV-6159] – The AutoMLTest.java test suite now runs correctly on a local mach...

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H2O Release 3.24 (Yates)
by Michal Kurka | April 02, 2019 H2O Release

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’ve introduced cross-version support for model import, added new features for model interpretation, provided much-improved support for reading data from Apache Hive, and included various algorithm and AutoML impr...

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Building AI/ML models on Lending Club Data, with H2O.ai — Part 1
by Karthik Guruswamy, Vinod Iyengar | March 28, 2019 Beginners , Community , Data Journalism , Data Science , Technical , Tutorials

Lending Club publishes its basic loan databases to the public and a full version to its customers — anonymized of course. You can find the download page from this link (screenshot below): The publicly downloadable loan data has various attributes — roughly 150+ columns that have categorical, numeric, text and date fields. It also has a ‘...

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AI/ML Model Scoring - What Good Looks Like in Production
by Karthik Guruswamy | March 10, 2019 H2O Driverless AI , Machine Learning , Technical

One of the main reasons why we build AI/Machine Learning models is for it to be used in production to support expert decision making. Whether your business is deciding what creatives your customers should be getting on emails or determining a product recommendation for a web page, AI/Models provide relevance/context to customers to drive ...

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Machine Learning with H2O – the Benefits of VMware
by Vinod Iyengar | March 06, 2019 Cloud , Community , H2O Driverless AI

This blog was originally posted by Justin Murray of VMware and can be accessed here. This brief article introduces a short 4.5 minute video that explains the reasons why VMware vSphere is a great platform for data scientists/engineers to use as their base operating platform. The video then demonstrates an example of this, showing a data...

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How to explain a model with H2O Driverless AI

The ability to explain and trust the outcome of an AI-driven business decision is now a crucial aspect of the data science journey. There are many tools in the marketplace that claim to provide transparency and interpretability around machine learning models but how does one actually explain a model? H2O Driverless AI provides robust inte...

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Boosting your ROI with AutoML & Automatic Feature Engineering
by Karthik Guruswamy | February 25, 2019 AutoML , Machine Learning

If your business has started using AI/ML tools or just started to think about it, this blog is for you. Whether you are a data scientist, VP of data science or a line of a business owner, you are probably wondering how AI will impact your organization in various ways or why your current strategies are not working somehow. If you are not ...

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What is Your AI Thinking? Part 3

In the past two posts we’ve learned a little about interpretable machine learning in general. In this post, we will focus on how to accomplish interpretable machine learning using H2O Driverless AI . To review, the past two posts discussed: Exploratory data analysis (EDA) Accurate and interpretable models Global explanations Local...

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8 Tips to Make AI Happen Without Getting Fired
by Ingrid Burton | February 15, 2019 H2O World

“AI is the fastest growing workload on the planet,” Mike Gualtieri of Forrester Research.Last week, during H2O World San Francisco, we had the privilege to hear featured speaker Mike Gualtieri from Forrester Research offer tips on how to make AI happen without getting fired. This knowledge, he explained, was acquired by talking to enterp...

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The Journey of Pi and AI: An AI conference with heart
by Thomas Ott | February 08, 2019 H2O World , Makers

I was in San Francisco this (past) week as part of H2O World 2019. I flew in the week before and took a red-eye flight back home right after the conference on Tuesday night. Like any technology conference, this one had fantastic presentations, training, and product roadmap presentations. We even live streamed it if you couldn’t be there i...

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Key Takeaways from the Gartner Magic Quadrant For Data Science & Machine Learning

The Gartner Magic Quadrant for Data Science and Machine Learning Platforms (Jan 2019) is out and H2O.ai has been named a Visionary. The Gartner MQ evaluates platforms that enable expert data scientists, citizen data scientists and application developers to create, deploy and manage their own advanced analytic models.H2O.ai Key Highlights...

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What is Your AI Thinking? Part 2

Explaining AI to the Business PersonWelcome to part 2 of our blog series: What is Your AI Thinking? We will explore some of the most promising testing methods for enhancing trust in AI and machine learning models and systems. We will also cover the best practice of model documentation from a business and regulatory standpoint.More Techniq...

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H2O New Year releases
by H2O.ai Team | January 18, 2019 H2O Release , H2O-3 , Python , R

There were two releases shortly after each other. First, on December 21st, there was a minor (fix) release 3.22.0.3 . Immediately followed by a more major release (but still on 3.22 branch) codename Xu, named after mathematician Jinchao Xu , whose work is focused on deep neural networks, besides many other fields of research.Of course, th...

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What is Your AI Thinking? Part 1

Explaining AI to the Business PersonExplainable 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 . Moreover, interpretability, fairness, and transparency of data-driven decision support sy...

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Finally, You Can Plot H2O Decision Trees in R
by Gregory Kanevsky | January 15, 2019

Creating and plotting decision trees (like one below) for the models created in H2O will be the main objective of this post: Figure 1. Decision Tree Visualization in R Decision Trees with H2O With release 3.22.0.1 H2O-3 (a.k.a. open source H2O or simply H2O) added to its family of tree-based algorithms (which already included DR...

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What Business Leaders Need to Know About AI
by Ingrid Burton | January 11, 2019 Beginners , Community , Data Journalism , Data Science

The interest around artificial intelligence (AI) is at an all-time fevered pitch right now, and it’s important to understand why.AI can solve real business problems and address very complex situations. Organizations and business leaders should start with the idea of how AI can help by identifying a business problem or use case that they c...

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Celebrating our community and wins!
by H2O.ai Team | January 11, 2019 Community , Machine Learning , Makers

The last year was an amazing year at H2O.ai. We organized two H2O World’s, gathering thousands of attendees in person and online both in New York and London. Throughout the year, we garnered multiple industry awards and honors for AI and machine learning, but our customers received awards as well for the work they are doing with our techn...

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