Skip to main content

Automated ML profiling and reporting tool

Project description

ML Profiler

ML Profiler is a lightweight Python library that automates machine learning profiling and reporting. It helps you understand your dataset, preprocess it, select models, evaluate performance, and generate explainability insights—all in one line.

🔧 Features

  • 📊 Data summary and missing value analysis
  • 🧼 Preprocessing suggestions (encoding, scaling)
  • 🧠 Auto model selection (classification/regression)
  • 📈 Model training and evaluation
  • 🔍 SHAP-based explainability
  • 📄 HTML report generation

🚀 Installation

pip install ml-profiler

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_profiler-0.3.1.tar.gz (5.6 kB view details)

Uploaded Source

Built Distribution

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

ml_profiler-0.3.1-py3-none-any.whl (7.3 kB view details)

Uploaded Python 3

File details

Details for the file ml_profiler-0.3.1.tar.gz.

File metadata

  • Download URL: ml_profiler-0.3.1.tar.gz
  • Upload date:
  • Size: 5.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.13.1

File hashes

Hashes for ml_profiler-0.3.1.tar.gz
Algorithm Hash digest
SHA256 f2ca7d53fc71b7760b4a40f701c5a15d60f9ccb3756e78d8b6bdd4a9f41b24b3
MD5 4260435292dffdd6a4c91f6d069563ff
BLAKE2b-256 01c76c3acee82e0253c0d9f7398bb683b059fa208803a75215f37ad216edd567

See more details on using hashes here.

File details

Details for the file ml_profiler-0.3.1-py3-none-any.whl.

File metadata

  • Download URL: ml_profiler-0.3.1-py3-none-any.whl
  • Upload date:
  • Size: 7.3 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.13.1

File hashes

Hashes for ml_profiler-0.3.1-py3-none-any.whl
Algorithm Hash digest
SHA256 563babaa4f1ad9a443a6d1d7f2649e4096ed8325a42d308a832107d22f73dfeb
MD5 e793bdbd2a04681b43f108686837fa79
BLAKE2b-256 1f08580d53e7c8d8321dbee3c08ebfc901eedde7531c89a979fd738597dd5c0e

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