Showing 7 open source projects for "issues"

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  • 1
    CleanVision

    CleanVision

    Automatically find issues in image datasets

    ...The quality of machine learning models hinges on the quality of the data used to train them, but it is hard to manually identify all of the low-quality data in a big dataset. CleanVision helps you automatically identify common types of data issues lurking in image datasets. This package currently detects issues in the raw images themselves, making it a useful tool for any computer vision task such as: classification, segmentation, object detection, pose estimation, keypoint detection, generative modeling, etc.
    Downloads: 0 This Week
    Last Update:
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  • 2
    Arize Phoenix

    Arize Phoenix

    Uncover insights, surface problems, monitor, and fine tune your LLM

    ...The toolset is designed to ingest model inference data for LLMs, CV, NLP and tabular datasets. It allows Data Scientists to quickly visualize their model data, monitor performance, track down issues & insights, and easily export to improve. Deep Learning Models (CV, LLM, and Generative) are an amazing technology that will power many of future ML use cases. A large set of these technologies are being deployed into businesses (the real world) in what we consider a production setting.
    Downloads: 13 This Week
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  • 3
    Cleanlab

    Cleanlab

    The standard data-centric AI package for data quality and ML

    ...This package helps you find label issues and other data issues, so you can train reliable ML models. All features of cleanlab work with any dataset and any model. Yes, any model: PyTorch, Tensorflow, Keras, JAX, HuggingFace, OpenAI, XGBoost, scikit-learn, etc. If you use a sklearn-compatible classifier, all cleanlab methods work out-of-the-box.
    Downloads: 0 This Week
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  • 4
    Dagster

    Dagster

    An orchestration platform for the development, production

    ...Centralize your metadata in one tool with built-in observability, diagnostics, cataloging, and lineage. Spot any issues and identify performance improvement opportunities.
    Downloads: 0 This Week
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    Build Agents and Models on One Platform

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  • 5
    Pandas Profiling

    Pandas Profiling

    Create HTML profiling reports from pandas DataFrame objects

    ...Mostly global details about the dataset (number of records, number of variables, overall missigness and duplicates, memory footprint). Comprehensive and automatic list of potential data quality issues (high correlation, skewness, uniformity, zeros, missing values, constant values, between others).
    Downloads: 0 This Week
    Last Update:
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  • 6
    data-diff

    data-diff

    Efficiently diff rows across two different databases

    ...Replicating data at scale, across hundreds of tables, with low latency and at a reasonable infrastructure cost is a hard problem, and most data teams we’ve talked to, have faced data quality issues in their replication processes. The hard truth is that the quality of the replication is the quality of the data. Since copying entire datasets in batch is often infeasible at the modern data scale, businesses rely on the Change Data Capture (CDC) approach of replicating data using a continuous stream of updates.
    Downloads: 0 This Week
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  • 7
    dbt-re-data

    dbt-re-data

    re_data - fix data issues before your users & CEO would discover them

    re_data is an open-source data reliability framework for the modern data stack. Currently, re_data focuses on observing the dbt project (together with underlaying data warehouse - Postgres, BigQuery, Snowflake, Redshift). Data transformations in re_data are implemented and exposed as models & macros in this dbt package. Gather all relevant outputs about your data in one place using our cloud. Invite your team and debug it easily from there. Go back in time, and see your past metadata. Set up...
    Downloads: 0 This Week
    Last Update:
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