2021 Blog Optimization 
DataKitchen
APRIL 13, 2021
Download the 2021 DataOps Vendor Landscape here. Read the complete blog below for a more detailed description of the vendors and their capabilities. DataOps is a hot topic in 2021. Observe, optimize, and scale enterprise data pipelines. . Varada – Self-optimizing cloud data virtualization platform. . Data breaks.
Dataiku
FEBRUARY 19, 2021
In this series, we're going to break up their key topics (trustworthy ML, human-in-the-loop ML, causality, and the connection between reinforcement learning and AutoML) so they're easy for you to digest as you aim to optimize your ML projects in 2021.
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Cloudera
DECEMBER 21, 2021
In working with thousands of customers deploying Spark applications, we saw significant challenges with managing Spark as well as automating, delivering, and optimizing secure data pipelines. New in 2021. Figure 2 – CDE product launch highlights in 2021. Figure 1: CDE service components and practitioner functions.
AWS Big Data
DECEMBER 17, 2024
First query response times for dashboard queries have significantly improved by optimizing code execution and reducing compilation overhead. We have enhanced autonomics algorithms to generate and implement smarter and quicker optimal data layout recommendations for distribution and sort keys, further optimizing performance.
Dataiku
FEBRUARY 10, 2021
In this series, we're going to break up their key topics (trustworthy ML, human-in-the-loop ML, causality, and the connection between reinforcement learning and AutoML) so they're easy for you to digest as you aim to optimize your ML projects in 2021.
Domino Data Lab
APRIL 29, 2021
Keras is optimized for idea expression. These new architectures are learned in a supervised manner by optimizing under changed conditions. Hydrology Power Optimization. AES leverages optimization and forecast models. He went on to talk about where Keras is now and what he sees for its future. Image from [link].
Dataiku
FEBRUARY 23, 2021
In this series, we're going to break up their key topics (trustworthy ML, human-in-the-loop ML, causality, and the connection between reinforcement learning and AutoML) so they're easy for you to digest as you aim to optimize your ML projects in 2021.
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