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ML Pipeline

A machine learning pipeline for Exploratory Data Analysis (EDA), data preprocessing, model training, and evaluation. This package helps to quickly analyze datasets, preprocess data, and train models like Random Forest or XGBoost with detailed evaluation metrics.

Features

  • Perform EDA and visualize data
  • Handle missing values and scale data
  • Encode categorical data
  • Train Random Forest or XGBoost models
  • Evaluate models using F1 score, R², MSE, etc.

Installation

You can install the package via pip:

pip install ml-pipeline

Metadata

Release files for ml-pipeline-jhansi 0.1.4

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for ml-pipeline-jhansi 0.1.4
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ml_pipeline_jhansi-0.1.4.tar.gz 7.4 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for ml-pipeline-jhansi 0.1.4
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ml_pipeline_jhansi-0.1.4-py3-none-any.whl Python 3 none any Details

Total release size: 16.2 kB

Release files / ml_pipeline_jhansi-0.1.4.tar.gz

Download URL ml_pipeline_jhansi-0.1.4.tar.gz
Size 7.4 kB
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Release files / ml_pipeline_jhansi-0.1.4-py3-none-any.whl

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Size 8.8 kB
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0.1.4 This release

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0.1.3

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