Showing 8 open source projects for "report"

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  • 1
    CML

    CML

    Continuous Machine Learning | CI/CD for ML

    ...Use it to automate development workflows, including machine provisioning, model training and evaluation, comparing ML experiments across project history, and monitoring changing datasets. CML can help train and evaluate models, and then generate a visual report with results and metrics, automatically on every pull request.
    Downloads: 3 This Week
    Last Update:
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  • 2
    Shapash

    Shapash

    Explainability and Interpretability to Develop Reliable ML models

    ...It provides several types of visualization that display explicit labels that everyone can understand. Data Scientists can more easily understand their models, share their results and easily document their projects in an HTML report. End users can understand the suggestion proposed by a model using a summary of the most influential criteria.
    Downloads: 2 This Week
    Last Update:
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  • 3
    Pandas Profiling

    Pandas Profiling

    Create HTML profiling reports from pandas DataFrame objects

    ...The pandas df.describe() function is handy yet a little basic for exploratory data analysis. pandas-profiling extends pandas DataFrame with df.profile_report(), which automatically generates a standardized univariate and multivariate report for data understanding. High correlation warnings, based on different correlation metrics (Spearman, Pearson, Kendall, Cramér’s V, Phik). Most common categories (uppercase, lowercase, separator), scripts (Latin, Cyrillic) and blocks (ASCII, Cyrilic). File sizes, creation dates, dimensions, indication of truncated images and existance of EXIF metadata. ...
    Downloads: 7 This Week
    Last Update:
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  • 4
    AIF360

    AIF360

    A comprehensive set of fairness metrics for datasets

    This extensible open source toolkit can help you examine, report, and mitigate discrimination and bias in machine learning models throughout the AI application lifecycle. We invite you to use and improve it. The AI Fairness 360 toolkit is an extensible open-source library containing techniques developed by the research community to help detect and mitigate bias in machine learning models throughout the AI application lifecycle.
    Downloads: 2 This Week
    Last Update:
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    Smart Business Texting that Generates Pipeline

    Create and convert pipeline at scale through industry leading SMS campaigns, automation, and conversation management.

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  • 5
    Deepchecks

    Deepchecks

    Test Suites for validating ML models & data

    ...More details about the existing checks and the parameters they can receive can be found in our API Reference. An ordered collection of checks, that can have conditions added to them. The Suite enables displaying a concluding report for all of the Checks that ran.
    Downloads: 0 This Week
    Last Update:
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  • 6
    MLJAR Studio

    MLJAR Studio

    Python package for AutoML on Tabular Data with Feature Engineering

    ...It abstracts the common way to preprocess the data, construct the machine learning models, and perform hyper-parameter tuning to find the best model. It is no black box, as you can see exactly how the ML pipeline is constructed (with a detailed Markdown report for each ML model).
    Downloads: 0 This Week
    Last Update:
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  • 7
    smclarify

    smclarify

    Fairness aware machine learning. Bias detection and mitigation

    Fairness Aware Machine Learning. Bias detection and mitigation for datasets and models. A facet is column or feature that will be used to measure bias against. A facet can have value(s) that designates that sample as "sensitive". Bias detection and mitigation for datasets and models. The label is a column or feature which is the target for training a machine learning model. The label can have value(s) that designates that sample as having a "positive" outcome. A bias measure is a function...
    Downloads: 0 This Week
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  • 8
    Convolution arithmetic

    Convolution arithmetic

    A technical report on convolution arithmetic in deep learning

    A technical report on convolution arithmetic in the context of deep learning. The code and the images of this tutorial are free to use as regulated by the licence and subject to proper attribution. The animations will be output to the gif directory. Individual animation steps will be output in PDF format to the pdf directory and in PNG format to the png directory.
    Downloads: 0 This Week
    Last Update:
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