Subject archive for "domino-product," page 3

Data Science

A Practitioner's Guide to Deep Learning with Ludwig

Joshua Poduska provides a distilled overview of Ludwig including when to use Ludwig’s command-line syntax and when to use its Python API.

By Josh Poduska7 min read

Data Science

Announcing Trial and Domino 3.5: Control Center for Data Science Leaders

Even the most sophisticated data science organizations struggle to keep track of their data science projects. Data science leaders want to know, at any given moment, not just how many data science projects are in flight but what the latest updates and roadblocks are when it comes to model development and what projects need their immediate attention.

By Domino8 min read

Data Science

Announcing Domino 3.4: Furthering Collaboration with Activity Feed

Our last release, Domino 3.3 saw the addition of two major capabilities: Datasets and Experiment Manager. “Datasets”, a high-performance, revisioned data store offers data scientists the flexibility they need to make use of large data resources when developing models. And “Experiment Manager” acts as a data scientist’s “modern lab notebook” for tracking, organizing, and finding everything tested over the course of their research.

By Domino2 min read

Data Science

Domino 3.3: Datasets and Experiment Manager

Our mission at Domino is to enable organizations to put models at the heart of their business. Models are so different from software — e.g., they require much more data during development, they involve a more experimental research process, and they behave non-deterministically — that organizations need new products and processes to enable data science teams to develop, deploy and manage them at scale.

By Domino5 min read

Data Science

Domino 3.0: New Features and User Experiences to Help the World Run on Models

This blog post introduces new Domino 3.0 features. Akansh Murthy is a Technical Product Manager at Domino and previously worked as a software engineer at Domino and Kareo.

By Akansh Murthy7 min read

Benchmark

Benchmarking NVIDIA CUDA 9 and Amazon EC2 P3 Instances Using Fashion MNIST

In this post, Josh Poduska, Chief Data Scientist at Domino Data Lab, writes about benchmarking NVIDIA CUDA 9 and Amazon EC2 P3 Instances Using Fashion MNIST. If interested in additional insight from Poduska, he will also be presenting "Managing Data Science in the Enterprise" at Strata New York 2018.

By Josh Poduska8 min read

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