Showing 2 open source projects for "reduce"

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    Train ML Models With SQL You Already Know

    BigQuery automates data prep, analysis, and predictions with built-in AI assistance.

    Build and deploy ML models using familiar SQL. Automate data prep with built-in Gemini. Query 1 TB and store 10 GB free monthly.
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    Custom VMs From 1 to 96 vCPUs With 99.95% Uptime

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    Live migration and automatic failover keep workloads online through maintenance. One free e2-micro VM every month.
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    lakeFS

    lakeFS

    lakeFS - Git-like capabilities for your object storage

    Increase data quality and reduce the painful cost of errors. Data engineering best practices using git-like operations on data. lakeFS is an open-source data version control for data lakes. It enables zero-copy Dev / Test isolated environments, continuous quality validation, atomic rollback on bad data, reproducibility, and more. Data is dynamic, it changes over time.
    Downloads: 3 This Week
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  • 2
    Diffgram

    Diffgram

    Training data (data labeling, annotation, workflow) for all data types

    ...Diffgram is a single application that will improve your data labeling and bring all aspects of training data under a single roof. Diffgram is world’s first truly open source training data platform that focuses on giving its users an unlimited experience. This is aimed to reduce your data labeling bills and increase your Training Data Quality. Training Data is the art of supervising machines through data. This includes the activities of annotation, which produces structured data; ready to be consumed by a machine learning model. Annotation is required because raw media is considered to be unstructured and not usable without it. ...
    Downloads: 3 This Week
    Last Update:
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