DataKitchen

APRIL 13, 2021

Read the complete blog below for a more detailed description of the vendors and their capabilities. Because it is such a new category, both overly narrow and overly broad definitions of DataOps abound. Bitbucket – Git code management. Git – A free and open-source distributed version control system. ModelOps/MLOps.

Testing 307

Testing Machine Learning Consulting Data Quality 307

erwin

APRIL 4, 2022

Data modelling data definition language (DDL) can now be integrated into a GitHub/Git repository via Mart. This integration provides: Easy integration with Git. The ability to push DDL into Git. The ability to push DDL into Git. Keep reading to see how to connect to Git repositories. Connecting to Git Repositories.

Modeling 52

Modeling Data Processing Data-driven Big Data 52

IBM Big Data Hub

MAY 18, 2023

We received the highest score in the “Current offering” category on the scorecard, the highest possible scores in the authoring, applications, and supporting products and services criteria, and the highest market presence score among all evaluated vendors. We are pleased that IBM has been named as a Leader in the Forrester Wave.

Reporting 92

Reporting Scorecard Predictive Modeling Machine Learning 92

Domino Data Lab

MAY 1, 2019

I attended the machine learning meetup and reached out to Mawer for the permissions to excerpt Mawer’s work for this blog post. Only the external/ and sample/ subdirectories are tracked by git. ? ??? Not synced with git. ? ??? external/ <- External data sources, will be synced with git ? ??? test_size: 0.25

Machine Learning 81

Machine Learning Testing Data Science Modeling 81

AWS Big Data

JUNE 1, 2023

In this blog post, we demonstrate how you can use DJL within Kinesis Data Analytics for Apache Flink for real-time machine learning inference. The data stream pipeline can involve multiple models for different purposes, such as classifying uploaded images into ecommerce categories of electronics, toys, fashion, and so on.

Deep Learning 62

Deep Learning Data Analytics Analytics Machine Learning 62

erwin

JUNE 7, 2022

This blog is based upon webcast which can be watched here. As with the part 1 of this blog series, the cloud is not nirvana. As we’ve seen in this blog, data modeling for a data warehouse is very different from doing one for an OLTP system. Related links: Like this blog? Like this blog? So please avoid snowflakes.

Data Warehouse 52

Data Warehouse Modeling Sales Data Lake 52

O'Reilly on Data

NOVEMBER 28, 2023

But that isn’t all the art that a company needs: “hero images” for blog posts, designs for reports and whitepapers, edits to publicity photos, and more are all necessary. The LLaMA-family models also fall into the “so-called open source” category that restricts what you can build. Is generative AI the answer? Perhaps not yet.

Enterprise 269

Enterprise Modeling Testing Reporting 269