Subject archive for "data-scientists," page 8

We have seen an explosion of interest among data scientists who want to use GPUs for training deep learning models. While the libraries to support this (e.g., keras, TensorFlow, etc) have become very powerful, data scientists are still plagued with configuration issues that limit their productivity.

In this Data Science Popup panel led by Michael Manapat, Product and Machine Learning at Stripe, we learn about practical applications of data science at Gusto, and instruction of practical data science at General Assembly. The panel members are Daniel Sternberg, Data Science and Engineering Lead at Gusto, and Kiefer Katovich, Department Chair for Data Courses at General Assembly.

This post describes how Domino uses Docker to solve a number of interconnected problems for data scientists and researchers, related to environment agility and reproducibility of work.

R and Python are both popular open source programming languages for data scientists. Each has its advantages for performing data science tasks. So, which one should you use? In this video, Eduardo Ariño de la Rubia, makes a case for each of them as the "best" language for data scientists.

We’re excited to announce support for Amazon’s X1 instances. Now in Domino, you can do data science on machines with 128 cores and 2TB of RAM — with one click:

It's the sixteenth anniversary of Joel Spolsky's "Joel Test," which he described as a "highly irresponsible, sloppy test to rate the quality of a software team."