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New Improvements in H2O 3.32.0.2
by Veronika Maurerova | December 17, 2020 H2O Release, XGBoost

There is a new minor release of H2O that introduces two useful improvements to our XGBoost integration: interaction constraints and feature interactions.Interaction ConstraintsFeature interaction constraints allow users to decide which variables are allowed to interact and which are not.Potential benefits: Better predictive performance...

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Introducing H2O Wave
by Jo-Fai Chow, Benjamin Cox | December 15, 2020 H2O Hydrogen Torch, H2O-3, Product Updates, Python

For almost a decade, H2O.ai has worked to build open source and commercial products that are on the leading edge of innovation in machine learning, from AutoML to Explainable AI . We are thrilled to announce the release of what we believe to be the future of AI Applications: H2O Wave . Wave is an open source, lightweight Python developmen...

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Grandmaster Series: The inspiring journey of the ‘Beluga’ of Kaggle World 🐋
by Parul Pandey | December 14, 2020 Kaggle, Machine Learning

In conversation with Gábor Fodor: A Data Scientist at H2O.ai and a Kaggle Competitions’ Grandmaster. In this series of interviews, I present the stories of established Data Scientists and Kaggle Grandmasters at H2O.ai , who share their journey, inspirations, and accomplishments. These interviews are intended to motivate and encourage othe...

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Automate your Model Documentation using H2O AutoDoc
by Parul Pandey | November 19, 2020 Data Science, H2O Driverless AI

Create model documentation for Supervised learning models in H2O-3 and Scikit-Learn — in minutes.The Federal Reserve’s 2011 guidelines state that without adequate documentation, model risk assessment and management would be ineffective. A similar requirement is put forward today by many regulatory and corporate governance bodies. Thus ...

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Mitos e verdades sobre o AutoML
by Alan Silva, Bruna Smith | November 10, 2020 AutoML, Beginners, Business, Community, Machine Learning

Todas as revoluções que tivemos até hoje, tanto as tecnológicas quanto industriais, possuem uma semelhança: elas estão ligadas à forma como os seres humanos lidam com as máquinas. Antes, os processos eram feitos de forma muito manual e, com o tempo, acabaram sofrendo uma evolução natural voltada para a automação. Com o aprendizado de máqu...

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Maximizing your Value from AI
by Eve-Anne Trehin | November 09, 2020 Business, Community, Machine Learning, Partners

Some organizations have already identified the benefits that can be gained from Artificial Intelligence and Data Science, bringing in talented resources to enable them to build AI models and solutions. But more often than not, the business doesn’t understand the capabilities and huge potential of AI well enough, nor the investments that a...

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AI in the Financial Industry: 8 Key Takeaways from the Bill.com + H2O.ai Fireside Chat
by Bruna Smith | November 05, 2020 Community, Customers, Financial Services

The current global pandemic crisis presents various challenges to businesses in all industries, including financial services institutions, who are monitoring and dealing with the effects of COVID-19 across the world. At a time of a pandemic, it is important that teams get together to share their insights and experience, with the goal of i...

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The Importance of Explainable AI
by H2O.ai Team | October 30, 2020 Community, Machine Learning Interpretability, Responsible AI

This blog post was written by Nick Patience, Co-Founder & Research Director, AI Applications & Platforms at 451 Research, a part of S&P Global Market Intelligence From its inception in the mid-twentieth century, AI technology has come a long way. What was once purely the topic of science fiction and academic discussion is now...

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Building an AI Aware Organization

Responsible AI is paramount when we think about models that impact humans, either directly or indirectly. All the models that are making decisions about people, be that about creditworthiness, insurance claims, HR functions, and even self-driving cars, have a huge impact on humans. We recently hosted James Orton, Parul Pandey, and Sudala...

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H2O on Kubernetes using Helm
by H2O.ai Team | October 16, 2020 H2O-3, Kubernetes, Technical

Deploying real-world applications using bare YAML files to Kubernetes is a rather complex task, and H2O is no exception. As demonstrated in one of the previous blog posts . Greatly simplified, a cluster of H2O open source machine learning nodes is brought up in the following manner: A headless service to make initial node discovery and ...

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Making AI a Reality
by Ellen Friedman | October 16, 2020 Business, Machine Learning, Machine Learning Interpretability

This blog post focuses on the content discussed in more depth in the free ebook “ Practical Advice for Making AI Part of Your Company’s Future”. Do you want to make AI a part of your company? You can’t just mandate AI. But you can lead by example.All too often, especially in companies new to AI and machine learning, team leaders may be ta...

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Combining the power of KNIME and H2O.ai in a single integrated workflow
by Rafael Coss, Stefan Pacinda | October 14, 2020 AutoML, Community, H2O Driverless AI, Partners, Technical, Tutorials

KNIME and H2O.ai , the two data science pioneers known for their open source platforms, have partnered to further democratize AI. Our approaches are about being open, transparent, and pushing the leading edge of AI. We believe strongly that AI is not for the select few but for everyone. We are taking another step in democratizing AI by ...

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The Challenges and Benefits of AutoML
by Eve-Anne Trehin | October 14, 2020 AutoML, H2O Driverless AI, Machine Learning, Responsible AI

Machine Learning and Artificial Intelligence have revolutionized how organizations are utilizing their data. AutoML or Automatic Machine Learning automates and improves the end-to-end data science process. This includes everything from cleaning the data, engineering features, tuning the model, explaining the model, and deploying it into p...

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H2O Release 3.32 (Zermelo)
by Michal Kurka | October 14, 2020 H2O Release, H2O-3

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 added RuleFit — an interpretable machine learning algorithm , introduced a new toolbox for model explainability, made Target Encoding work for all classes of problems, and integrated it in our AutoML framewor...

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5 Key Elements to Detecting Fraud Quicker With AI
by Ashrith Barthur | October 13, 2020 Financial Services, Fraud Detection, H2O Driverless AI

The number of transactions using electronic financial instruments has been increasing by about 23% year over year. The global COVID-19 pandemic has only accelerated that process. Electronic means have become the primary vehicle of how people purchase their goods. With this sudden increase in transactions, fraud detection systems are stres...

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Empowering Snowflake Users with AI using SQL
by Vinod Iyengar, Yves Laurent | October 12, 2020 Community, Machine Learning, Partners, Technical, Tutorials

At H2O.ai we work with many enterprise customers, all the way from Fortune 500 giants to small startups. What we heard from all these customers as they embark on their data science and machine learning journey is the need to capture and manage more data cost-effectively, and the ability to share that data across their organization to mak...

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3 Ways to Ensure Responsible AI Tools are Effective

Since we began our journey making tools for explainable AI (XAI) in late 2016, we’ve learned many lessons, and often the hard way. Through headlines, we’ve seen others grapple with the difficulties of deploying AI systems too. Whether it’s: a healthcare resource allocation system that likely discriminated against millions of black peop...

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Accelerating AI Transformation in Healthcare
by H2O.ai Team | October 07, 2020 Business, Community, H2O Driverless AI, Machine Learning

The healthcare industry is evolving rapidly with volumes of data and increasing challenges. Early adopters of AI and machine learning in the healthcare space have embraced new data-driven initiatives and are reaping the benefits not only in terms of patient care but also in their own operations. Hospitals, physicians, and laboratories can...

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5 Key Considerations for Machine Learning in Fair Lending

This month, we hosted a virtual panel with industry leaders and explainable AI experts from Discover, BLDS, and H2O.ai to discuss the considerations in using machine learning to expand access to credit fairly and transparently and the challenges of governance and regulatory compliance. The event was moderated by Sri Ambati, Founder and CE...

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The Benefits of Budget Allocation with AI-driven Marketing Mix Models
by Michael Proksch | September 17, 2020 AutoML, Business, Customers, GBM, GLM, Machine Learning, Solutions

Excerpt of the white paper: “The Latest in AI Technologies Reinvent Media and Marketing Analytics @ Allergan” Authors: Akhil Sood, Associate Director @ Marketing Sciences, Allergan Dr. Michael Proksch, Senior Director @ H2o.ai Vijay Raghavan, Associate Vice President @ Marketing Sciences, AllerganIntroductionThe call for accountability in...

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My Experience at the World’s Best AI Company
by Jo-Fai Chow | September 15, 2020 Makers

Blog post by Spencer Loggia When H2O announced that remote work would continue through the summer due to Covid-19, I was a little disappointed. I expected that it would be difficult to connect with others as a new employee, especially as an intern. My internship now comes to an end, and I realize how completely wrong I was. I’ve met and w...

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What it is like to intern at H2O.ai
by Jo-Fai Chow | September 15, 2020 Makers

Blog post by Jasmine Parekh Let’s be honest, 2020 is not going to go down as a glory year in history, unless something absolutely miraculous happens in the next few months. Generations of highschoolers down the line will sit in history class learning about the pandemic that halted the world. In the face of the virus, everyone around the w...

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Desmistificando a Inteligência Artificial e seu papel no sucesso dos negócios
by Bruna Smith | September 14, 2020 Business, Makers

A Inteligência Artificial tem sido um termo bastante utilizado atualmente, mas será que todos sabem, na prática, o que ela significa e como se beneficiar dessa tecnologia inovadora? Assim como toda buzzword, a IA também gera muitos mitos. Entre eles, a crença de que a aprendizagem de máquinas irá substituir o trabalho dos cientistas de da...

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Modèles NLP avec BERT
by Badr Chentouf | September 02, 2020 H2O Driverless AI, NLP

H2O Driverless AI 1.9 vient de sortir, et je vous propose une série d’articles sur les dernières fonctionnalités innovantes de cette solution d’Automated Machine Learning, en commençant par l’implémentation de BERT pour les tâches NLPBERT , ou “Bidirectional Encoder Representations from Transformers” est considéré aujourd’hui comme l’éta...

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Exploring the Next Frontier of Automatic Machine Learning with H2O Driverless AI
by Jo-Fai Chow | July 28, 2020 AutoML, H2O Driverless AI

At H2O.ai, it is our goal to democratize AI by bridging the gap between the State-of-the-Art (SOTA) in machine learning and a user-friendly, enterprise-ready platform. We have been working tirelessly to bring the SOTA from Kaggle competitions to our enterprise platform Driverless AI since its very first release. The growing list of Driver...

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In a World Where… AI is an Everyday Part of Business
by Ellen Friedman | July 22, 2020 Company, H2O Driverless AI, Machine Learning Interpretability

Imagine a dramatically deep voice-over saying “In a world where…” This phrase from old movie trailers conjures up all sorts of futuristic settings, from an alien “world where the sun burns cold”, a Mad Max “world without gas” to a cyborg “world of the not too distant future”.Often the epic science fiction or futuristic stories also have a...

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Running Sparkling Water in Kubernetes
by Jakub Hava | July 10, 2020

Sparkling Water can now be executed inside the Kubernetes cluster. Sparkling Water provides a Beta version of Kubernetes support in a form of nightlies. Both Kubernetes deployment modes, cluster and client, are supported. Also, both Sparkling Water backends and all clients are also ready to be tested. Sparkling Water in Kubernetes is ...

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From GLM to GBM – Part 2

How an Economics Nobel Prize could revolutionize insurance and lending Part 2: The Business Value of a Better ModelIntroductionIn Part 1 , we proposed better revenue and managing regulatory requirements with machine learning (ML). We made the first part of the argument by showing how gradient boosting machines (GBM), a type of ML, can mat...

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A Inteligência Artificial está transformando e alavancando negócios. Entenda como e por quê
by Daniel Garbuglio | June 26, 2020

Você sabia que inteligência artificial e machine learning não são conceitos novos? Pois eles surgiram pela primeira vez em 1956 na universidade de Dartmouth, nos Estados Unidos, mas vêm mudando e evoluindo significativamente ao longo do tempo. Hoje, a quantidade de dados que uma empresa dispõe para análise é gigantesca e seu crescimento é...

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On-Ramp to AI
by Rafael Coss | June 11, 2020

The path to democratize AI starts with one class Artificial Intelligence (AI) is like a superhighway, it’s moving fast, evolving, and growing quickly. Like most things in life, data scientists are not born with AI and Machine Learning (ML) knowledge. They learn it. Learning is a journey. At H2O.ai, we are on a mission to democratize AI...

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From GLM to GBM - Part 1

How an Economics Nobel Prize could revolutionize insurance and lending Part 1: A New Solution to an Old ProblemIntroductionInsurance and credit lending are highly regulated industries that have relied heavily on mathematical modeling for decades. In order to provide explainable results for their models, data scientists and statisticians i...

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Sparkling Water 3.30.0.3 is out
by Jakub Hava | June 04, 2020 H2O-3, Sparkling Water

Sparkling Water is about making machine learning simple, speedy, and scalable with Apache Spark. This blog provides an overview of the following new features: No H2O Client on Spark Driver Speedups Automatic String conversion to Categoricals No H2O Client on Spark DriverPreviously, Sparkling Water always started worker nodes eith...

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Are All Your AI and ML Models Wrong?
by James Orton | May 05, 2020 Machine Learning, Makers

We are living in unprecedented times. Our society and economy are experiencing shocks beyond anything we have seen in living history. Beyond the human cost, there is a data science and machine learning elephant in the room (hopefully 2 meters away): Are your predictive models still doing the job you expect them to do?The challenge here i...

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Lessons of COVID-19 and Moving Forward: Key Takeaways
by Ingrid Burton | May 01, 2020 AI4Good, Community, Company, Data Science

This week, we hosted our second virtual panel focused on how AI can empower healthcare organizations to make better decisions and save lives. Improved forecasting and predictions lead to higher chances in managing and mitigating adverse events, such as the COVID-19 pandemic. I’m proud to acknowledge that H2O.ai is committed to helping cus...

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Running H2O cluster on a Kubernetes cluster
by H2O.ai Team | April 14, 2020 H2O-3, Kubernetes

H2O is an open-source, in-memory platform for distributed, scalable machine learning. A perfect match for deployment on a Kubernetes cluster, the very modern way of deploying, serving & scaling applications. With the major release 3.30.0.1, released in Q1 2020, H2O obtained first class Kubernetes support .This article explains how t...

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H2O Release 3.30 (Zahradnik)
by Michal Kurka | April 07, 2020 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 Generalized Additive Models, added an option to build many models in parallel on segments of your dataset, improved support for deploying on Kubernetes, upgraded XGBoost with newly added...

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Brief Perspective on Key Terms and Ideas in Responsible AI
by Benjamin Cox | April 02, 2020 Data Science, Explainable AI, Machine Learning, Responsible AI

INTRODUCTIONAs fields like explainable AI and ethical AI have continued to develop in academia and industry, we have seen a litany of new methodologies that can be applied to improve our ability to trust and understand our machine learning and deep learning models. As a result of this, we’ve seen several buzzwords emerge. In this short po...

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Three Ways Data and AI is Helping Against COVID19
by Niki Athanasiadou | April 01, 2020 AI4Good, Data Science, Healthcare, Machine Learning

We are in the midst of a global crisis that epidemiologists have warned us about. As of today, 180 countries and sovereign regions have confirmed cases of patients infected with COVID19 (from here ). Putting aside evidence that indicates the virulence of the disease could be much worse, the fast spread of the virus and the presence of hi...

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Modelling Currently Infected Cases of COVID-19 Using H2O Driverless AI
by Marios Michailidis | March 30, 2020 Healthcare

In response to the wake of the pandemic called COVID-19, H2O.ai organized a panel discussion to cover AI in healthcare, and some best practices to put in place in order to achieve better outcomes. The attendees had many questions that we did not have the time to cover thoroughly throughout the course of that 1-hour discussion. We hope ...

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Deploying Models to Maximise the Impact of Machine Learning — Part 1
by Stefan Pacinda, John Spooner | March 29, 2020 H2O Driverless AI, Machine Learning, ModelOps

Introduction to the 4 key pillars of considerations for model deployment (1st part of a blog series)So you have built a machine learning (ML) model which delivers a high level of accuracy and does not overfit. What value does it have now? Well, at the moment, nothing, zero, diddly squat. There is no economic value in a machine learning mo...

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Igniting the AI in Healthcare Community
by David Engler | March 28, 2020 AI4Good, Community, Data Science, Healthcare

Yesterday we held our first Community Discussion on AI in Healthcare. Our CEO and founder, Sri Ambati led the discussion between Niki Athanasiadou, Marios Michailidis, one of our Grandmasters , and myself. We had nearly 1,300 participants registered from over 45 countries, and over half of those joined live others are viewing the replay. ...

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COVID-19: Doing Good with Data + AI
by David Engler, Marios Michailidis | March 26, 2020 AI4Good, Data Science, Healthcare, Machine Learning, Time Series

During times of severe societal strain, individuals have historically shown an inclination to offer aid and assistance. Often these sacrifices have been at great cost to life or livelihood. In other cases, the efforts have been seemingly more mundane but nevertheless still essential. The efforts of the over 10,000 women code breakers of W...

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Take Your Pega CRM on the Road to AI Transformation
by Yves Laurent | March 24, 2020 Business, Cloud, H2O Driverless AI, Solutions

How well does your company know its customers and prospects? Are your people empowered with relevant information when they interact with clients? What guides your employees at every step of the customer journey? Every successful company depends on how well it can address each of these questions. Investments in Customer Relationship Manage...

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How H2O.ai is Reinventing Healthcare with AI
by Parul Pandey | March 23, 2020 AI4Good, Data Science, Healthcare

H2O.ai is hosting a virtual Meetup on AI and Healthcare: Best Practices for Better Outcomes. Join us on 26th March, for a community discussion to collaborate with us and leading healthcare organizations to share ideas and best practices including predicting hospital staffing needs, ICU transfers, as well as sepsis detection and more. Reg...

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Summary of a Responsible Machine Learning Workflow

A paper resulting from a collaboration between H2O.AI and BLDS, LLC was recently published in a special “Machine Learning with Python” issue of the journal, Information (https://www.mdpi.com/2078-2489/11/3/137). In “A Responsible Machine Learning Workflow with Focus on Interpretable Models, Post-hoc Explanation, and Discrimination Testing...

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It is a privilege to serve the world in its hour of need – H2O.ai response to the COVID-19 pandemic
by Sri Ambati | March 19, 2020 AI4Good, Community, Data Science, Healthcare, Machine Learning

During the COVID-19 pandemic, our world, our nations, states, counties, cities and communities face an unprecedented challenge with an urgent need to help our citizens and ultimately our national and global economy. At highest risk are senior citizens, at-risk populations (individuals with immunodeficiency, hypertension, diabetes) and our...

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Health Outcomes and the Miracle of Data
by David Engler | March 16, 2020 AI4Good, Healthcare, Machine Learning

In 1846, a physician named Ignatz Semmelweis, located at the Allgemeine Krankenhaus in Vienna, faced a dire healthcare crisis. He observed that the maternity ward in his own hospital (as well as those in other area hospitals) had a maternal mortality rate of over 15%. That is, one out of every six mothers who came to his hospital to give ...

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Detecting Money Laundering Networks Using H2O Driverless AI
by Parul Pandey, Ashrith Barthur, Sandip Sharma | March 05, 2020 Anti-Money Laundering, Data Science, Financial Services, H2O Driverless AI

Note: Dr. Ashrith Barthur (Principal Security Scientist, H2O.ai) and Sandip Sharma (Director of Solution Engineering, H2O.ai) will be speaking about solving money laundering and other real-world problems using machine learning at our upcoming webinar. You can grab a spot here. Artificial Intelligence has evolved from being a buzz word t...

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A Letter to the Makers at H2O.ai
by Sri Ambati | March 05, 2020 Makers

To TeamAll,Many of you have already seen this alert from me in different variations over the last few weeks. Some of you are already remote and following some of these precautions.Starting today please make all meetings default to virtual or remote. Use Zoom, Webex, Slack, FaceTime, WhatsApp and WeChat to keep in touch with your teammates...

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Insights From the New 2020 Gartner Magic Quadrant For Cloud AI Developer Services

We are excited to be named a Visionary in the new Gartner Magic Quadrant for Cloud AI Developer Services (Feb 2020), and have been recognized for both our completeness of vision and ability to execute in the emerging market for cloud-hosted artificial intelligence (AI) services for application developers. This is the second Gartner MQ tha...

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AI & ML Platforms: My Fresh Look at H2O.ai Technology

2020: A new year, a new decade, and with that, I’m taking a new and deeper look at the technology H2O.ai offers for building AI and machine learning systems. I’ve been interested in H2O.ai since its early days as a company (it was 0xdata back then) in 2014. My involvement had been only peripheral, but now I’ve begun to work with this comp...

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Interview with Patrick Hall | Machine Learning, H2O.ai & Machine Learning Interpretability

Audio Link: In this episode of Chai Time Data Science , Sanyam Bhutani interviews Patrick Hall, Sr. Director of Product at H2O.ai. Patrick has a background in Math and has completed a MS Course in Analytics.In this interview they talk all about Patrick’s journey into ML, ML Interpretability and his journey at H2O.ai, how his work has ev...

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Key Takeaways from the 2020 Gartner Magic Quadrant for Data Science and Machine Learning

We are named a Visionary in the Gartner Magic Quadrant for Data Science and Machine Learning Platforms (Feb 2020). We have been positioned furthest to the right for completeness of vision among all the vendors evaluated in the quadrant. So let’s walk you through the key strengths of our machine learning platforms. Automatic Machine Learn...

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Blink: Data to AI/ML Production Pipeline Code in Just a Few Clicks
by Karthik Guruswamy | February 11, 2020 H2O Driverless AI, Machine Learning, Python, Technical

You have the data and now want to build a really really good AI/ML model and deliver to production. There are three options available today: Write the code yourself in a Jupyter notebook/R Studio etc., for training/validation and dev-ops model handoff. You decided to do the feature engineering also. Build your own features like above,...

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Speed up your Data Analysis with Python’s Datatable package
by Parul Pandey | February 05, 2020 Data Munging, Data Science, Datatable, H2O Driverless AI

A while ago, I did a write up on Python’s Datatable library . The article was an overview of the datatable package whose focus is on big data support and high performance. The article also compared datatable’s performance with the pandas’ library on certain parameters. This is the second article in the series with a two-fold objective: ...

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Parallel Grid Search in H2O
by H2O.ai Team | February 04, 2020 Data Science, H2O-3, Machine Learning, Python, R, R-Bloggers, Recommendations, Technical

H2O-3 is, at its core, a platform for distributed, in-memory computing. On top of the distributed computation platform, the machine learning algorithms are implemented. At H2O.ai, we design every operation, be it data transformation, training of machine learning models or even parsing to utilize the distributed computation model. In ord...

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The Super Bowl and Data Science: Changing the NFL with the Power of Machine Learning
by Rafael Coss | January 31, 2020 Data Science, H2O-3, Kaggle, Machine Learning

Super Bowl LIV came and went. The San Francisco 49ers vs the Kansas City Chiefs. Personally, being from the The Bay, I was rooting for the 49ers, but you can’t always get what you want. Whoever came out on top, though, we were all looking forward to a great game full of fantastic plays and the kind of gridiron tenacity where players lay i...

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Grandmaster Series: How a Passion for Numbers Turned This Mechanical Engineer into a Kaggle Grandmaster
by Parul Pandey | January 23, 2020 AutoML, Community, Company, Data Science, H2O Driverless AI, Kaggle, Makers, NLP

In conversation with Sudalai Rajkumar: A Kaggle Double Grandmaster and a Data Scientist at H2O.aiIt is rightly said that one should never seek praise. Instead, let the effort speak for itself. One of the essential traits of successful people is to never brag about their success but instead keep learning along the way. In the data science ...

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How H2O propels data scientists ahead of itself: enhancing Driverless AI models with advanced options, recipes and visualizations
by Gregory Kanevsky | January 06, 2020

H2O.ai engineers continually innovate and introduce new techniques by adopting latest research, working on cutting edge use cases, and participating in and winning machine learning competitions like Kaggle. But thanks to the explosion of AI research and applications even the most advanced automated machine learning platform like H2O Drive...

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