- Leaders, Changes, and Trends in Gartner 2020 Magic Quadrant for Data Science and Machine Learning Platforms - Feb 24, 2020.
The Gartner 2020 Magic Quadrant for Data Science and Machine Learning Platforms has the largest number of leaders ever. We examine the leaders and changes and trends vs previous years.
- Do You Trust and Understand Your Predictive Models? - Feb 4, 2020.
To help practitioners make the most of recent and disruptive breakthroughs in debugging, explainability, fairness, and interpretability techniques for machine learning read “An Introduction to Machine Learning Intrepretability Second Edition”. Download this report now.
- H2O Framework for Machine Learning - Jan 6, 2020.
This article is an overview of H2O, a scalable and fast open-source platform for machine learning. We will apply it to perform classification tasks.
- Gainers, Losers, and Trends in Gartner 2019 Magic Quadrant for Data Science and Machine Learning Platforms - Feb 11, 2019.
We compare Gartner 2019 MQ for Data Science, Machine Learning Platforms to its previous versions and identify notable changes for leaders and challengers, including RapidMiner, KNIME, TIBCO, Alteryx, Dataiku, SAS, and MathWorks.
- Automated Machine Learning in Python - Jan 18, 2019.
An organization can also reduce the cost of hiring many experts by applying AutoML in their data pipeline. AutoML also reduces the amount of time it would take to develop and test a machine learning model.
- Data Science For Business: 3 Reasons You Need To Learn The Expected Value Framework - Jul 26, 2018.
This article highlights the importance of learning the expected value framework in data science, covering classification, maximization and testing.
- Gainers and Losers in Gartner 2018 Magic Quadrant for Data Science and Machine Learning Platforms - Feb 27, 2018.
We compare Gartner 2018 Magic Quadrant for Data Science, Machine Learning Platforms vs its 2017 version and identify notable changes for leaders and challengers, including IBM, SAS, RapidMiner, KNIME, Alteryx, H2O.ai, and Domino.
- Deep Learning in H2O using R - Jan 22, 2018.
This article is about implementing Deep Learning (DL) using the H2O package in R. We start with a background on DL, followed by some features of H2O's DL framework, followed by an implementation using R.
- Driverless AI: Fast, Accurate, Interpretable AI - Jan 9, 2018.
H2O.ai recently launched Driverless AI, which speeds up data science workflows by automating feature engineering, model tuning, ensembling, and model deployment.
- H2O World 2017: The best of data science, AI, and business transformation, Dec 4-5, Mountain View - Oct 18, 2017.
The flagship H2O World is back to bring together the best of data science, AI, Machine Learning, and business transformation. Spaces are limited, so get a spot at 50% off w. code KDNUGGETS by Oct 21, 2017.
- Using Machine Learning to Predict and Explain Employee Attrition - Oct 4, 2017.
Employee attrition (churn) is a major cost to an organization. We recently used two new techniques to predict and explain employee turnover: automated ML with H2O and variable importance analysis with LIME.
- Why Every Company Needs a Digital Brain - Jul 11, 2017.
As emerging technologies like AI/machine learning are adopted across different parts of the business, enterprises require a “digital brain” to coordinate those efforts and generate systemic intelligence.
- Improving Zillow Zestimate with 36 Lines of Code - Jul 7, 2017.
We built this project as a quick and easy way to leverage some of the amazing technologies that are being built by the data science community!
- DataScience.com, H2O.ai Partner to Bring AI Capabilities to Enterprise Data Science Teams - Jun 23, 2017.
DataScience.com Platform customers can now easily deploy artificial intelligence and deep learning models built with H2O.ai’s open source AI platform.
- For AI Engineers/Data Scientists: Implementing Enterprise AI course - Nov 7, 2016.
This unique course that is focussed on AI Engineering / AI for the Enterprise. Created in partnership with H2O.ai , the course uses Open Source technology to work with AI use cases. It is offered online and also in London and Berlin, starting January 2017.
- Deep Learning for Internet of Things Using H2O - Apr 6, 2016.
H2O is feature-rich open source machine learning platform known for its R and Spark integration and it’s ease of use. This is an overview of using H2O deep learning for data science with the Internet of Things.
- Top 10 Deep Learning Tips & Tricks - Dec 14, 2015.
Deep Learning has been at the forefront of data science innovations throughout 2015. Dr. Arno Candel offers help through some valuable tips.
- Spark + Deep Learning: Distributed Deep Neural Network Training with SparkNet - Dec 4, 2015.
Training deep neural nets can take precious time and resources. By leveraging an existing distributed batch processing framework, SparkNet can train neural nets quickly and efficiently.
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- H2O World 2015 – Day 3 Highlights - Nov 20, 2015.
Highlights from talks delivered by machine learning experts from Fast Forward Labs, H20.ai, Kaiser and Macy's at H2O World held in Mountain View.
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- H2O World 2015 – Day 2 Highlights - Nov 19, 2015.
Highlights from talks delivered by machine learning experts from H20.ai, Jawbone, Stanford, Quora & PayPal at H2O World held in Mountain View.
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- H2O World 2015 – Day 1 Highlights - Nov 16, 2015.
Highlights from talks and tutorials delivered by machine learning experts at H2O World 2015 held in Mountain View.
- H2O World 50% off for 24 hours only – Open Source Machine Learning - Sep 23, 2015.
Join machine learning industry leaders, H2O customers, and community in a day of H2O training and two days of talks. 50% OFF valid for 24 hours only.
- API for Prediction and Machine Learning: poll results and analysis - Sep 1, 2015.
APIs are set procedures which provide easy to use, automated, robust solution to the recurring programming challenges. Here, we analyzed major players in the big data domain are providing machine learning APIs.
- Join machine learning leaders at H2O World, Nov 9-11, early bird rates now - Aug 28, 2015.
Join H2O for 3-day machine learning conference, hear from top experts including Hilary Mason, Rob Tibshirani, and Stephen Boyd, participate in a hackathon and hands-on data science training.
- H2O Deep Learning Webinar - Aug 24, 2015.
H2O.ai is a Google-scale open source machine learning engine for R and Big Data. This webinar introduces Distributed Deep Learning concepts, implementation and results from recent developments.
- Decision Boundaries for Deep Learning and other Machine Learning classifiers - Jun 15, 2015.
H2O, one of the leading deep learning framework in python, is now available in R. We will show how to get started with H2O, its working, plotting of decision boundaries and finally lessons learned during this series.
- R leads RapidMiner, Python catches up, Big Data tools grow, Spark ignites - May 25, 2015.
R is the most popular overall tool among data miners, although Python usage is growing faster. RapidMiner continues to be most popular suite for data mining/data science. Hadoop/Big Data tools usage grew to 29%, propelled by 3x growth in Spark. Other tools with strong growth include H2O (0xdata), Actian, MLlib, and Alteryx.
- CRN Big Data Business Analytics Companies - May 12, 2015.
Data, Analytics, and Intelligence play a key role in CRN Big Data 100 in 2015. New additions include predictive analytics firms Knime, Logi Analytics, Looker, Luminoso, Predixion, RapidMiner, and Salesforce.
- Deep Learning to Fight Crime - Apr 22, 2015.
We look at how using Deep Learning, Spark, and H2O Machine Learning platform can be used to analyze and predict crime in San Francisco and Chicago.
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- Interview: Ted Dunning, MapR on Apache Mahout & Technology Landscape in ML - Mar 3, 2015.
We discuss Apache Mahout, its comparison with Spark and H2O, trends, advice, desired qualities in data scientists and more.
- Interview: Arno Candel, H2O.ai on the Journey from Physics to Machine Learning - Jan 22, 2015.
We discuss Arno’s career path, transition from Physics to Machine Learning, talent gap in Big Data, advice and more.
- Interview: Arno Candel, H20.ai on How to Quick Start Deep Learning with H2O - Jan 21, 2015.
We discuss H2O use cases, resources to start using H2O for Deep Learning, evolution of High Performance Computing (HPC) and the future of HPC.
- Interview: Arno Candel, H2O.ai on the Basics of Deep Learning to Get You Started - Jan 20, 2015.
We discuss how Deep Learning is different from the other methods of Machine Learning, unique characteristics and benefits of Deep Learning, and the key components of H2O architecture.
- Surfing the Big Data Wave at H2O World - Nov 25, 2014.
Recent H2O World event showcased its open-source, scalable machine learning in the cloud, intended for people familiar with R but limited by its scalability. H2O can run on Hadoop and also on Apache Spark.
- Additions to KDnuggets Directory in October - Nov 3, 2014.
17 new meetings including MLConf, H2O World, Deep Learning Innovation Summit, BigDataWeek; Analytics tools from InfoCaptor, analytixBASE, Wizard, uxColor, and more.
- H2O World, Open Source Machine Learning Meeting, Nov 18-19, Mountain View - Oct 27, 2014.
H2O World (Nov 18-19, Mountain View) is where the users of the very popular Open Source Machine Learning Engine H2O gather to share their knowledge and know-how to build Smart Applications.
- Learn how Sparkling Water brings H2O Deep Learning to Apache Spark, Oct 29 Webinar - Oct 6, 2014.
Sparkling Water is the latest innovation to combine two best-of-breed open source technologies Apache Spark and H2O. Learn how to setup your own Sparkling Water environment at Oct 29 Webinar.
- Deep Learning with H2O, May 21 Webcast - May 1, 2014.
H2O is Google-scale open source machine learning engine for R and Big Data. Learn how Deep Learning in H2O is unlocking never before seen performance for prediction - May 21.