GCP + GPUs 💙 Kubernetes (and Tensorflow)
When I wrote how to deploy Tensorflow on Kubernetes a couple of weeks ago, I took advantage of AWS as my cloud substrate. A reader commented and asked for instructions to setup the GPU cluster on the Google Cloud Platform. I said I would answer to Vikas, so here it is, a method to deploy Kubernetes with GPUs on the Google Cloud Platform. RequirementsTo replicate this post, you will need: Understan
How Zendesk Serves TensorFlow Models in Production
How We Started With TensorFlowAt Zendesk we are developing a series of machine learning products, the most recent of which is Answer Bot. It uses machine learning to interpret user questions and responds with relevant knowledge base articles. When a customer has a question, complaint or enquiry, they may submit their request online. Once their request is received, Answer Bot will analyse the reque
Introducing Tensorflow Ruby API
TensorFlow is an extraordinary open source software library for numerical computation using data flow graphs. It was originally developed by researchers and engineers working on the Google Brain Team within Google’s Machine Intelligence research organisation for the purpose of conducting machine learning and deep neural networks research, but the system is general enough to be applicable in a wide
An LSTM Odyssey
This week I read LSTM: A Search Space Odyssey. It’s an excellent paper that systematically evaluates the different internal mechanisms of an LSTM (long short-term memory) block by disabling each mechanism in turn and comparing their performance. We’re going to implement each of the variants in TensorFlow and evaluate their performance on the Penn Tree Bank (PTB) dataset. This will obviously not be
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TensorFlow Object Detection on Azure — Part 2: Using Kubernetes to run distributed TensorFlow…
Tensorflow in Kubernetes in 88 MB
