Let's nitpick about the physics of Stranger Things, not its ending Feedback has seen all the fuss about the finale of Stranger Things, but would like to point out that if we're going to dissect the plot, we have bigger things to worry about In common, it seems, with a substantial fraction of the human species, Feedback spent part of our holiday watching the final episodes of Stranger Things . We laughed, we cried, we wondered if it would have even more endings than The Return of the King (it did). As is almost inevitable these days, a group of fans vocally disliked the finale, and went so far as to create a conspiracy theory about it. According to "Conformity Gate" (don't blame us, we didn't name it), the finale wasn't the real finale - despite lasting more than 2 hours, costing an enormous amount of money and being shown in cinemas. No, a super-secret final episode was going to air in January, which would reveal the true ending.

We all have stuff that we've bought ourselves -- or asked others to buy for us -- that makes us happy, even if we suspect our friends may not understand why it's so great. It could be a $100-plus coffee cup that keeps your liquid at the exact right temperature. Or a video game that you've been playing for years. Or a hair styler that is way expensive but would make you look fabulous. We asked the staff of The Verge what some of their guilty pleasures are, and the braver among us volunteered some answers. I'm hesitant to call it a "guilty" pleasure because I have used this $550 (or more) GE Opal 2.0 ice machine every day for nearly a full year and not once have I felt guilt about spending such an obscene amount of cash on a kitchen gadget that does exactly one thing.

Spark is an up and coming new big data technology; it's a whole lot faster andeasier than existing Hadoop-based solutions. H2O does state-of-the-art MachineLearning algorithms over Big Data – and does them Fast. We are happy toannounce that H2O now has a basic integration with Spark – Sparkling Water! This is a "deep" integration – H2O can convert Spark RDDs to H2O DataFrames andvice-versa directly. The conversion is fully in-memory and in-process, anddistributed and parallel as well.

Last week at H2O World San Francisco, H2O.ai announced a number of improvements to Driverless AI, H2O, Sparkling Water, and AutoML, as well as several new partnerships for Driverless AI. The improvements provide incremental improvements across the platform, while the partnerships reflect H2O.ai expanding their audience and capabilities. This piece is intended to provide guidance to data analysts, data scientists, and analytic professionals working on including machine learning in their workflows. H2O.ai has integrated H2O Driverless AI with Alteryx Designer; the connector is available for download in the Alteryx Analytics Gallery. This will permit Alteryx users to implement more advanced and automatic machine learning algorithms into analytic workflows in Designer, as well as doing automatic feature engineering for their machine learning models.

We recently sat down with Kuba and Pavel from H2O to discuss how you can easily lift your Spark notebooks to the next level by adding some H20 to it using their open source Sparkling Water project. In this first part of the interview, we cover the conceptual principles behind Sparkling water and discuss some existing use case implementations. Senior Software Engineer at H2O.ai Machine learning engineer at H2O.ai, Software engineer, Writer Please use the Contact Form on this blog or our twitter feed to send us your questions, or to suggest future episode topics you would like us to cover. Tackler of advanced Cloud and Hadoop challenges in a world of open-source technologies.

We are in an age in which machine learning has increasing importance in our daily lives. Machine learning is put into action whenever your mobile map application automatically reminds you to leave for your next appointment because of unusual traffic situations. Besides personal assistants on your cell phones, wearable sport devices use machine-learning algorithms to propose personal training plans, and banks depend on accurate machine-learning models to detect malicious transactions. Healthcare, for instance, has also started to find helpful patterns in medical data using machine learning. Modern technologies allow for close monitoring of a patient's condition through a large volume of data provided by a number of sensors.

The Sparkling Water project is nearing its one-year anniversary, which means Michal Malohlava, our main contributor, has been very busy for the better part of this past year. The Sparkling Water project combines H2O machine-learning algorithms with the execution power of Apache Spark. This means that the project is heavily dependent on two of the fastest growing machine-learning open source projects out there. With every major release of Spark or H2O there are API changes and, less frequently, major data structure changes that affect Sparkling Water. Throw Cloudera releases into the mix, and you have a plethora of git commits dedicated to maintaining a few simple calls to move data between the different platforms.

H2O.ai Melds Machine Learning with Spark, Via Sparkling Water 2.0 by - Jul. 01, 2016 The Renaissance Continues for Open Source Artificial Intelligence Baidu Delivers a Hardened Open Source Deep Learning Tool Google Launches a Slew of Open Source Parsers, to Work with 40 Languages IBM's Massive Spark Initiatives Include an Offering for Data Scientists In recent interviews here on OStatic, found here and here, we have explored the efforts of H2O.ai, formerly known as Oxdata, which has steadily been carving out a niche with its open source software for big data analysis and machine learning. You can get the main H2O platform and Sparkling Water, a package that works with Apache Spark, by simply downloading them. You can run them on clusters powered by Amazon Web Services (AWS) and others for just a few hundred dollars, putting powerful artificial intelligence muscle in reach of everyone. Now, H2O.ai has announced the availability of Sparkling Water 2.0. Sparkling Water 2.0 builds off the popularity of Sparkling Water, H2O.ai's API for Apache Spark, with additional features and functionality.

H2O.ai Melds Machine Learning with Spark, Via Sparkling Water 2.0 by - Jul. 01, 2016 The Renaissance Continues for Open Source Artificial Intelligence Baidu Delivers a Hardened Open Source Deep Learning Tool Google Launches a Slew of Open Source Parsers, to Work with 40 Languages IBM's Massive Spark Initiatives Include an Offering for Data Scientists Google's Custom Chip Can Accelerate Machine Learning Jobs In recent interviews here on OStatic, found here and here, we have explored the efforts of H2O.ai, formerly known as Oxdata, which has steadily been carving out a niche with its open source software for big data analysis and machine learning. You can get the main H2O platform and Sparkling Water, a package that works with Apache Spark, by simply downloading them. You can run them on clusters powered by Amazon Web Services (AWS) and others for just a few hundred dollars, putting powerful artificial intelligence muscle in reach of everyone. Now, H2O.ai has announced the availability of Sparkling Water 2.0. Sparkling Water 2.0 builds off the popularity of Sparkling Water, H2O.ai's API for Apache Spark, with additional features and functionality.

Thanks to Michal Malohlava, Amy Wang, and Avni Wadhwa of H20.ai for providing the following guest post about building ML apps using Sparkling Water and Apache Spark on CDH. The Sparkling Water project is nearing its one-year anniversary, which means Michal Malohlava, our main contributor, has been very busy for the better part of this past year. The Sparkling Water project combines H2O machine-learning algorithms with the execution power of Apache Spark. This means that the project is heavily dependent on two of the fastest growing machine-learning open source projects out there. With every major release of Spark or H2O there are API changes and, less frequently, major data structure changes that affect Sparkling Water.