Skip to main content

🔮 MLchemy – The Magic Wand for Machine Learning Predictions 🪄✨

Project description

MLchemy

🔮 MLchemy – The Magic Wand for Machine Learning Predictions 🪄✨

MLchemy is a lightweight yet powerful Python library designed for seamless regression and classification predictions. Built with efficiency and simplicity in mind, MLchemy allows you to harness the power of machine learning without the complexity of deep learning frameworks.

🔥 Why MLchemy?

Pure ML – No deep learning, just robust machine learning algorithms.
Plug & Predict – Simple API for quick and accurate predictions.
Versatile – Supports both regression & classification tasks.
Lightweight – No unnecessary dependencies, just what you need.
Scalable – Works for small datasets & large-scale applications.
Kaggle-Proven Tricks – Packed with advanced techniques used by top Kaggle Grandmasters.

🚀 Install & Get Started

pip install mlchemy

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

mlchemy-0.0.2.tar.gz (15.1 kB view details)

Uploaded Source

Built Distribution

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

mlchemy-0.0.2-py3-none-any.whl (15.5 kB view details)

Uploaded Python 3

File details

Details for the file mlchemy-0.0.2.tar.gz.

File metadata

  • Download URL: mlchemy-0.0.2.tar.gz
  • Upload date:
  • Size: 15.1 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.11.7

File hashes

Hashes for mlchemy-0.0.2.tar.gz
Algorithm Hash digest
SHA256 adcb0fdad09d9e99f06248e26757b22c489695999952d0aa2d9d18392570798e
MD5 6a2e539db24d92d19561704888f4d879
BLAKE2b-256 7f8fb9ed499ab17567bfcdf67242478eb422b7ee52361759d138f9b82bc6bf5c

See more details on using hashes here.

File details

Details for the file mlchemy-0.0.2-py3-none-any.whl.

File metadata

  • Download URL: mlchemy-0.0.2-py3-none-any.whl
  • Upload date:
  • Size: 15.5 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.11.7

File hashes

Hashes for mlchemy-0.0.2-py3-none-any.whl
Algorithm Hash digest
SHA256 c20b97573a9c824afd19120dcd9efe055d20ec91fec6016fde315e06e003ea81
MD5 90da2ca30d391e097e60e2732d3993ef
BLAKE2b-256 092240fc59f050ee24568ae2b4c5fe0d1bb0c2a93af528d253a2f3e61880bafa

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