phData

MAY 25, 2023

In a perfect world, Microsoft would have clients push even more storage and compute to its Azure Synapse platform. Snowflake was originally launched in October 2014, but it wasn’t until 2018 that Snowflake became available on Azure. This ensures the maximum amount of Snowflake consumption possible.

Power BI 84

Power BI Analytics Analytics Azure 84

Cambridge Intelligence

OCTOBER 19, 2023

In this post, we’ll take a look at some of the factors you could investigate, and introduce the six databases our customers work with most often: Amazon Neptune ArangoDB Azure Cosmos DB JanusGraph Neo4j TigerGraph Why these six graph databases?

Database 59

Database Azure SQL Analytics 59

IBM Journey to AI blog

NOVEMBER 13, 2023

Developed internally at Google and released to the public in 2014, Kubernetes has enabled organizations to move away from traditional IT infrastructure and toward the automation of operational tasks tied to the deployment, scaling and managing of containerized applications (or microservices ).

Machine Learning 134

Machine Learning Machine Learning ML ML 134

Heartbeat

FEBRUARY 27, 2023

AWS, Google Cloud, and Azure are a few well-known cloud service providers that provide pre-built GANs and DRL frameworks for creating and deploying models on their cloud platforms. These frameworks can be useful for speeding up training and utilizing powerful GPUs and TPUs.

Machine Learning 52

Machine Learning Machine Learning Deep Learning Deep Learning 52

DagsHub

OCTOBER 23, 2024

Popular data lake solutions include Amazon S3 , Azure Data Lake , and Hadoop. BLEU on the WMT 2014 English- to-German translation task, improving over the existing best results, including ensembles, by over 2 BLEU. Tooling : Apache Tika , ElasticSearch , Databricks , and AWS Glue for metadata extraction and management.

Machine Learning 52

Machine Learning Machine Learning AI AI 52

ODSC - Open Data Science

JANUARY 29, 2024

GANs, introduced in 2014 paved the way for GenAI with models like Pix2pix and DiscoGAN. While AWS is usually the winner when it comes to data science and machine learning, it’s Microsoft Azure that’s taking the lead for prompt engineering job descriptions.

Data Science 52

Data Science Machine Learning Machine Learning Natural Language Processing 52

The MLOps Blog

OCTOBER 20, 2023

In 2014, Project Jupyter evolved from IPython. Some of the most widely adopted tools in this space are Deepnote , Amazon SageMaker , Google Vertex AI , and Azure Machine Learning. Before them, we had IPython, which was integrated into IDEs such as Spyder that tried to mimic the way RStudio or Matlab worked. Aside neptune.ai

SQL 52

SQL Database Data Scientist Python 52