Data Science Blog | Data Engineering

Accelerating model velocity through Snowflake Java UDF integration

Over the next decade, the companies that will beat competitors will be “model-driven” businesses. These companies often undertake large data...

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Simplify data access and publish model results in Snowflake using Domino Data Lab

Introduction Arming data science teams with the access and capabilities needed to establish a two-way flow of information is one critical...

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The Curse of Dimensionality

Guest Post by Bill Shannon, Founder and Managing Partner of BioRankings Danger of Big Data Big data is the rage. This could be lots of rows (samples)...

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Machine Learning in Production: Software Architecture

Special thanks to Addison-Wesley Professional for permission to excerpt the following "Software Architecture" chapter from the book, Machine Learning...

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Themes and Conferences per Pacoid, Episode 7

Paco Nathan covers recent research on data infrastructure as well as adoption of machine learning and AI in the enterprise. Introduction Welcome...

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Creating Multi-language Pipelines with Apache Spark or Avoid Having to Rewrite spaCy into Java

In this guest post, Holden Karau, Apache Spark Committer, provides insights on how to create multi-language pipelines with Apache Spark and avoid...

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Data Science vs Engineering: Tension Points

This blog post provides highlights and a full written transcript from the panel, “Data Science Versus Engineering: Does It Really Have To Be This Way?

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Collaboration Between Data Science and Data Engineering: True or False?

This blog post includes candid insights about addressing tension points that arise when people collaborate on developing and deploying models....

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Themes and Conferences per Pacoid, Episode 1

Introduction: New Monthly Series! Welcome to a new monthly series! I’ll summarize highlights from recent industry conferences, new open source...

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Docker, but for Data

Aneesh Karve, Co-founder and CTO of Quilt, visited the Domino MeetUp to discuss the evolution of data infrastructure. This blog post provides a...

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New G3 Instances in AWS - Worth it for Machine Learning?

We benchmarked AWS’s new G3 instances for deep learning tasks and found they significantly outperform the older P2 instances. The new G3 instances...

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Data Scientists are Analysts are Software Engineers

In this Data Science Popup session, W. Whipple Neely, Director of Data Science at Electronic Arts, explains why data scientists have responsibilities...

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Data Science on AWS: Benefits and Common Pitfalls

More than two years ago, we wrote about the misguided fear of the cloud among many enterprise companies. How quickly things change! Today, every...

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Building a Model is the Least Important Part of Your Job

In this Data Science Popup session, Kimberly Shenk, Director of Data Science Solutions at Domino Data Lab, explains why building models is the least...

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Deep Learning on GPUs without the Environment Setup

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...

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