Tag archives: spark

In this blog post, we will see how we can use reverse image search based on (unsupervised) convolutional neural networks to make the analysis of satellite/aerial pictures both more efficient and simpler. After reading this post, you will be able to find similar objects in a large aerial/satellite images and from there develop your own GIS statistical applications (i.e. to count all white cars in your neighborhood, identify specific road markings or kind of trees, etc. ).

Note:  This blog post was written as a collaboration between Kensu.io and H2O.ai and the blog content was initially posted on on blog.H2O.ia.  You can either read it here, or continue your reading on its original publication page.

In the space of Data Science development in enterprises, two outstanding ...

In this blog, we will finally give an answer to THE question:  R, Python, Scala, Spark, Tensorflow, etc...  What is the best one to answer data science questions?  The question itself is totally absurd, but they are so many people asking it on social network that we find it worth to finally answer the recurrent question using a scientific methodology.  At the end of this blog, you will find a quantitative answer comparing the computing time of each language/library for fitting the exact same Generalized Linear Model (GLM).  Many features matter in the choice of a language/library, among them , the computing and developing time are for sure very important criteria.

Note: This blog post was initially written for the blog of Kensu.io, You can either read it here, or continue your reading on its original publication page.

This blog shows how to perform scalable geospatial data analysis using Geotrellis, Apache Spark, Sparkling-Water and the Spark-Notebook.

As a benchmark for this blog, we use ...