Skip to main content

A package for ML Pipeline with Streamlit dashboard

Project description

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

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

ml_pipeline_jhansi-0.1.3.tar.gz (7.4 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

ml_pipeline_jhansi-0.1.3-py3-none-any.whl (8.8 kB view details)

Uploaded Python 3

File details

Details for the file ml_pipeline_jhansi-0.1.3.tar.gz.

File metadata

  • Download URL: ml_pipeline_jhansi-0.1.3.tar.gz
  • Upload date:
  • Size: 7.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.12.7

File hashes

Hashes for ml_pipeline_jhansi-0.1.3.tar.gz
Algorithm Hash digest
SHA256 a4ae3653e3dc34e0209bd9e5e25eadcd5626926990468f5b430957eb4c5aa2e8
MD5 a639b6fce04aecf8e082811c735af96f
BLAKE2b-256 2ded43b8ed66afb00ac3e463486865ee0eb785efe44f5bc0dd1fc4721962a7e9

See more details on using hashes here.

File details

Details for the file ml_pipeline_jhansi-0.1.3-py3-none-any.whl.

File metadata

File hashes

Hashes for ml_pipeline_jhansi-0.1.3-py3-none-any.whl
Algorithm Hash digest
SHA256 26d3ad6d406f5cadf05ce5fb9f06bca64c96401b5e5511fe405a073658aca2ed
MD5 c6e81267ec67759ce6e1a7dde8297b74
BLAKE2b-256 654bc77af3917c3a7f110965c4e84acb1f830338450db63288fd1dcf334e18a0

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page