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-0.1.4.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-0.1.4-py3-none-any.whl (8.8 kB view details)

Uploaded Python 3

File details

Details for the file ml_pipeline_jhansi-0.1.4.tar.gz.

File metadata

  • Download URL: ml_pipeline_jhansi-0.1.4.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-0.1.4.tar.gz
Algorithm Hash digest
SHA256 1a3b647542c52f985a604751cc67f6a486496973c8452508a8e59593f31abb77
MD5 73e5dfa11d91929b51b8bd2718c31e14
BLAKE2b-256 6e11b0ddf3ac0ad30e9b9b7eb9e5fc42fc6f656f1f052dd0e2423f7b83e452c9

See more details on using hashes here.

File details

Details for the file ml_pipeline_jhansi-0.1.4-py3-none-any.whl.

File metadata

File hashes

Hashes for ml_pipeline_jhansi-0.1.4-py3-none-any.whl
Algorithm Hash digest
SHA256 7d67650d139abad303f8f2aca0b6729a3ca4c103f076bb51cbb9c09aa2d5a569
MD5 afcc28f1f8d93f4cb35a185338d9d4a4
BLAKE2b-256 687648ab83ec43a170b1455fb209ad038603c78a728378b9f0ce401af35b9efd

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