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Image Processing in Python

Image Processing in ...

Editor’s note: This post is part of the Silicon Valley Data Science Trainspotting series, a deep dive into the visual and audio detection components of the SVDS Caltrain project. Let them know your favorite part of the series and make comments on the original article here. The first step in developing our Caltrain project was creating a proof of […]

Introduction to Trainspotting

Introduction to Trai...

This was originally posted on the Silicon Valley Data Science blog. At Silicon Valley Data Science, we have a slight obsession with the Caltrain. Our interest stems from the fact that half of our employees rely on the Caltrain to get to work each day. We also want to give back to the community, and […]

Implementing a CNN for Text Classification in Tensorflow

Implementing a CNN f...

The full code is available on Github. In this post we will implement a model similar to Kim Yoon’s Convolutional Neural Networks for Sentence Classification. The model presented in the paper achieves good classification performance across a range of text classification tasks (like Sentiment Analysis) and has since become a standard baseline for new text […]

RNNs in Tensorflow, a Practical Guide and Undocumented Features

RNNs in Tensorflow, ...

In a previous tutorial series I went over some of the theory behind Recurrent Neural Networks (RNNs) and the implementation of a simple RNN from scratch. That’s a useful exercise, but in practice we use libraries like Tensorflow with high-level primitives for dealing with RNNs. With that using an RNN should be as easy as […]

Data Science from Cyberspace #1

Data Science from Cy...

By: Alex Perrier – ODSC data science team contributor Every week we bring you a selection of the best data science articles we found floating around Cyberspace. Writing an R package from scratch In the Python vs R debate one argument in favor of R is the amazing diversity and richness of R packages. In […]