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During re:Invent 2020 we announced Amazon Redshift ML(Preview) which makes it easy for SQL users to create, train, and deploy ML models using familiar SQL commands. Amazon Redshift ML allows you to use your data in Amazon Redshift with Amazon SageMaker(a fully managed ML service), without requiring you to become experts in ML. - Source: dev.to / 2 months ago
BigQuery is a serverless big data warehouse available as a part of Google Cloud Platform. It's highly scalable, meaning that it can process tiny datasets as well as petabytes of data in seconds, using more cloud capacity as needed. (However, due to BigQuery's distributed architecture, you can't possibly expect it to have a sub-second query response time.). - Source: dev.to / 2 months ago
Alternatively, you can look into Google Cloud BigQuery (https://cloud.google.com/bigquery). There is a limit on how much data that can be processed per month with a free account although they do provide a $300 credit. They have a public GitHub repos data set here: https://console.cloud.google.com/marketplace/product/github/github-repos. This is an example on how the dataset can be used:... - Source: Reddit / about 2 months ago
"Google Cloud’s databases and analytics products such as BigQuery, Dataflow, Pub/Sub and Firestore brought Theta Labs unlimited scale and performance, allowing them to: ...". - Source: Reddit / about 2 months ago
Https://cloud.google.com/bigquery#section-8 - Store all programmatic log levels on Google Bigquery, Build and deploy a propensity to purchase a model for predicting customer purchasing behavior using BigQuery ML and AI Platform. - Source: Reddit / 17 days ago
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Jupyter - Project Jupyter exists to develop open-source software, open-standards, and services for interactive computing across dozens of programming languages. Ready to get started? Try it in your browser Install the Notebook.