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How Much is My Property Worth?
Note : this is a guest blog post by Jaafar Almusaad .How Much is My Property Worth?This is the million-dollar question – both figuratively and literally. Traditionally, qualified property valuers are tasked to answer this question. It’s a lengthy and costly process, but more critically, it’s inconsistent and largely subjective. Mind you, ...
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Parallel Grid Search in H2O
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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H2O New Year releases
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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How This AI Tool Breathes New Life Into Data Science
Ask any data scientist in your workplace. Any Data Science Supervised Learning ML/AI project will go through many steps and iterations before it can be put in production. Starting with the question of “Are we solving for a regression or classification problem?” Data Collection & Curation Are there Outliers? What is the Distribu...
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H2O4GPU now available in R
In September, H2O.ai released a new open source software project for GPU machine learning called H2O4GPU . The initial release (blog post here ) included a Python module with a scikit-learn compatible API, which allows it to be used as a drop-in replacement for scikit-learn with support for GPUs on selected (and ever-growing) algorithms. ...
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Stacked Ensembles and Word2Vec now available in H2O!
Prepared by: Erin LeDell and Navdeep Gill MathJax.Hub.Config({ tex2jax: {inlineMath: [['$','$'], ['\\(','\\)']]} }); Stacked Ensembles ensemble <- h2o.stackedEnsemble(x = x, y = y, training_frame = train, base_models = my_models) Python:ensemble = H2OStackedEnsembleEstimator(base_models=my_models) ensemble.train(x=x, y=y, training...
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Behind the scenes of CRAN
(Just from my point of view as a package maintainer.) New users of R might not appreciate the full benefit of CRAN and new package maintainers may not appreciate the importance of keeping their packages updated and free of warnings and errors. This is something I only came to realize myself in the last few years so I thought I would write...
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sparklyr: R interface for Apache Spark
This post is reposted from Rstudio’s announcement on sparklyr – Rstudio’s extension for Spark Connect to Spark from R. The sparklyr package provides a complete dplyr backend. Filter and aggregate Spark datasets then bring them into R for analysis and visualization. Use Spark’s distributed machine learning library from R. Create...
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Hyperparameter Optimization in H2O: Grid Search, Random Search and the Future
“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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Red herring bites
At the Bay Area R User Group in February I presented progress in big-join in H2O which is based on the algorithm in R’s data.table package. The presentation had two goals: i) describe one test in great detail so everyone understands what is being tested so they can judge if it is relevant to them or not; and ii) show how it scales with...
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Fast csv writing for R
R has traditionally been very slow at reading and writing csv files of, say, 1 million rows or more. Getting data into R is often the first task a user needs to do and if they have a poor experience (either hard to use, or very slow) they are less likely to progress. The data.table package in R solved csv import convenience and speed in 2...
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Compressing Zip Codes with Generalized Low Rank Models
This tutorial introduces the Generalized Low Rank Model (GLRM) [1 ], a new machine learning approach for reconstructing missing values and identifying important features in heterogeneous data. It demonstrates how to build a GLRM in H2O that condenses categorical information into a numeric representation, which can then be used in other mo...
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