Cloudera

OCTOBER 3, 2022

You’ve found an awesome data set that you think will allow you to train a machine learning (ML) model that will accomplish the project goals; the only problem is the data is too big to fit in the compute environment that you’re using. Tell us if this sounds familiar. You do have a few options though. So what do you do? Prerequisites.

Machine Learning 90

Machine Learning Data Science Datasets Python 90

Data Engineering Podcast

JUNE 24, 2019

In this episode he explains his motivation for creating a new workflow engine that marries the needs of data engineers and data scientists, how it helps to smooth the handoffs between teams working on data projects, and how the design lets you focus on what you care about while it handles the failure cases for you.

Data Engineering 100

Data Engineering Data Engineer Engineering Data Science 100

Data Engineering Podcast

SEPTEMBER 30, 2019

Summary Building an end-to-end data pipeline for your machine learning projects is a complex task, made more difficult by the variety of ways that you can structure it. In this episode Tom Goldenberg explains how it works, how it is being used at Quantum Black for customer projects, and how it can help you structure your own.

Data Pipeline 100

Data Pipeline Machine Learning Media Data 100

Data Engineering Podcast

OCTOBER 28, 2019

In this episode he explains his motivation for creating a product for data management, how the programming model simplifies the work of building testable and maintainable pipelines, and his vision for the future of data programming. And for your machine learning workloads, they just announced dedicated CPU instances.

Building 100

Building Data Pipeline Programming Language Metadata 100

Cloudera

OCTOBER 26, 2022

?. It’s no secret that advancements like AI and machine learning (ML) can have a major impact on business operations. Cloudera has seen a lot of opportunity to extend even more time saving benefits specifically to data scientists with the debut of Applied Machine Learning Prototypes (AMPs).

Machine Learning 75

Machine Learning Project Deep Learning Data Science 75

Cloudera

APRIL 27, 2023

Each iteration requires more compute and the limitation imposed by Moore’s Law quickly moves that task from single compute instances to distributed compute. To accomplish this, OpenAI has employed Ray to power the distributed compute platform to train each release of the GPT models.

Machine Learning 76

Machine Learning Python Deep Learning Architecture 76

Cloudera

NOVEMBER 17, 2021

In recognition of the diverse workload that data scientists face, Cloudera’s library of Applied ML Prototypes (AMPs) provide Data Scientists with pre-built reference examples and end-to-end solutions, using some of the most cutting edge ML methods, for a variety of common data science projects. Today, the sexy is starting to lose its shine.

Machine Learning 123

Machine Learning Algorithm Data Science Retail 123