Using The Azure Data Science VM With GPUs

Jennifer Marsman has some tips and tricks around using the Azure Data Science Virtual Machine on an instance running with GPU support:

To get GPU support, you need both hardware with GPUs in a datacenter, as well as the right software – namely, a virtual machine image that includes GPU drivers so you can use the GPU.

The biggest tip is to use the Deep Learning Virtual Machine!  The provisioning experience has been optimized to filter to the options that support GPU (the NC series – see below), which make it easier to set it up correctly.

Read on for the rest of the advice.

Related Posts

P-Hacking and Multiple Comparison Bias

Patrick David has a great article on hypothesis testing, p-hacking, and multiple comparison bias: The most important part of hypothesis testing is being clear what question we are trying to answer. In our case we are asking:“Could the most extreme value happen by chance?”The most extreme value we define as the greatest absolute AMVR deviation from […]

Read More

Feature And Text Classification Using Naive Bayes In R

I wrap up my series on the Naive Bayes class of algorithms, finally writing some code along the way: Now we’re going to look at movie reviews and predict whether a movie review is a positive or a negative review based on its words. If you want to play along at home, grab the data set, […]

Read More

Categories

June 2018
MTWTFSS
« May Jul »
 123
45678910
11121314151617
18192021222324
252627282930