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Integrating VSCode editor into H2O Wave
by Martin Turoci | August 18, 2022 H2O Hydrogen Torch , H2O Wave , Tutorials

Let’s have a look at how to provide our users with a truly amazing experience when we need to allow them to edit pieces of code or configuration. We will use one of the most popular and well-known code editors called Monaco editor which powers VSCode. The resulting app will have the editor on the left side and a markdown card on the righ...

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5 Tips for Improving Your H2O Wave Apps
by Martin Turoci | August 09, 2022 H2O Wave , Tutorials

Let’s quickly uncover a few simple tips that are quick to implement and have a big impact. Do not recreate navigation, update it The most common error I see across the Wave apps is ugly navigation that seems to be laggy. Laggy navigation. The reason for this behavior is that we want to save the clicked value and set it e...

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Comprehensive Guide to Image Classification using H2O Hydrogen Torch

In this article, we will learn how to build state-of-the-art models in computer vision and natural language processing within a couple of minutes using H2O Hydrogen Torch. Introduction to H2O Hydrogen Torch H2O Hydrogen Torch (HT) aims to simplify building and deploying deep learning models for a wide range of tasks in computer vision...

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A Quick Introduction to PyTorch: Using Deep Learning for Stock Price Prediction

Torch is a scalable and efficient deep learning framework. It offers flexibility and speed to build large scale applications. It also includes a wide range of libraries for developing speech, image, and video-based applications. The basic building block of Torch is called a tensor. All the operations defined in Torch use a tensor. Ok, l...

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How to Create Your Spotify EDA App with H2O Wave

In this article, I will show you how to build a Spotify Exploratory Data Analysis (EDA) app using H2O Wave from scratch.H2O Wave is an open-source Python development framework for interactive AI apps. You do not need to know Flask, HTML, CSS, etc. H2O Wave has ready-to-use user-interface components and charts, including dashboard templa...

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Install H2O Wave on AWS Lightsail or EC2

Note : this blog post was first published on Thomas’ personal blog Neural Market Trends . I recently had to set up H2O’s Wave Server on AWS Lightsail and build a simple Wave App as a Proof of Concept. If you’ve never heard of H2O Wave then you have been missing out on a new cool app development framework. We use it at H2O to build AI-ba...

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Introducing DatatableTon - Python Datatable Tutorials & Exercises
by Rohan Rao | September 20, 2021 Datatable , H2O-3 , Python , Tutorials

Datatable is a python library for manipulating tabular data. It supports out-of-memory datasets, multi-threaded data processing and has a flexible API.If this reminds you of R’s data.table , you are spot on because Python’s datatable package is closely related to and inspired by the R library.The release of v1.0.0 was done on 1st July,...

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Visualizing Large Datasets with H2O-3
by Parul Pandey | September 09, 2021 H2O-3 , Tutorials

Exploratory data analysis is one of the essential parts of any data processing pipeline. However, when the magnitude of data is high, these visualizations become vague. If we were to plot millions of data points, it would become impossible to discern individual data points from each other. The visualized output in such a case is pleasing ...

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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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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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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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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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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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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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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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Use H2O.ai on Azure HDInsight
by H2O.ai Team | April 18, 2017 Cloud , Sparkling Water , Technical , Tutorials

This is a repost from this article on MSDN. We’re hosting an upcoming webinar to present you how to use H2O on HDInsight and to answer your questions. Sign up for our upcoming webinar on combining H2O and Azure HDInsight. We recently announced that H2O and Microsoft Azure HDInsight have integrated to provide Data Scientists with a Lead...

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Indexing 1 Billion Time Series with H2O and ISax
by H2O.ai Team | November 11, 2016 Solutions , Technical , Tutorials

At H2O, we have recently debuted a new feature called ISax that works on time series data in an H2O Dataframe. ISax stands for Indexable Symbolic Aggregate ApproXimation, which means it can represent complex time series patterns using a symbolic notation and thereby reducing the dimensionality of your data. From there you can run H2O’s ML...

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Hyperparameter Optimization in H2O: Grid Search, Random Search and the Future
by H2O.ai Team | June 16, 2016 R-Bloggers , Technical , Tutorials

“Good, better, best. Never let it rest. ‘Til your good is better and your better is best.” – St. Jerome tl;drH2O now has random hyperparameter search with time- and metric-based early stopping. Bergstra and Bengio[1] write on p. 281: Compared with neural networks configured by a pure grid search, we find that random search over the s...

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Spam Detection with Sparkling Water and Spark Machine Learning Pipelines
by H2O.ai Team | June 15, 2016 Sparkling Water , Technical , Tutorials

This short post presents the “ham or spam” demo, which has already been posted earlier by Michal Malohlava , using our new API in latest Sparkling Water for Spark 1.6 and earlier versions, unifying Spark and H2O Machine Learning pipelines. It shows how to create a simple Spark Machine Learning pipeline and a model based on the fitted pipe...

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