Domino Data Lab

APRIL 6, 2021

Editors Note: This article was originally posted on Patterson Consulting’s blog and can be found at [link] and has been republished with permission. Why Do We Need Ray? However, much of the load can be partitioned into smaller tasks and distributed over a large cluster. We could start as follows.

Data Science 81

Data Science Optimization Machine Learning Modeling 81

Domino Data Lab

FEBRUARY 12, 2020

Dean Wampler provides a distilled overview of Ray, an open source system for scaling Python systems from single machines to large clusters. If you are interested in additional insights, register for the upcoming Ray Summit. If you want a more in-depth technical introduction to Ray, see ?this Introduction.

Experimentation 137

Experimentation Modeling Data Science Management 137

Domino Data Lab

AUGUST 9, 2021

With the right tools, your data science teams can focus on what they do best – testing, developing and deploying new models while driving forward-thinking innovation. In general terms, a model is a series of algorithms that can solve problems when given appropriate data. It’s most helpful in analyzing structured data.

Modeling 111

Modeling Deep Learning Machine Learning Statistics 111

Cloudera

OCTOBER 26, 2022

Among the top benefits of ML, 59% of decision makers cite time savings, 54% cite cost savings, and 42% believe ML enables employees to focus on innovation as opposed to manual tasks. Data practitioners are at the top of the list of employees who are now able to put more focus on innovation. . What are AMPs and why do they help?

Machine Learning 74

Machine Learning Deep Learning Cost-Benefit Forecasting 74