ataozarslan/PyCaret_Tutorial

This repository includes a general informations and examples about how to make a machine learning model just a few lines of code in Python using PyCaret package.

PyCaret Tutorial

You can read the Turkish Instructions about this workflow on LinkedIn.

What is PyCaret and when to use?

• PyCaret is an open-source, low-code machine learning library in Python that automates machine learning workflows. It is an end-to-end machine learning and model management tool that exponentially speeds up the experiment cycle and makes you more productive.
• Compared with the other open-source machine learning libraries, PyCaret is an alternate low-code library that can be used to replace hundreds of lines of code with a few lines only. This makes experiments exponentially fast and efficient. PyCaret is essentially a Python wrapper around several machine learning libraries and frameworks, such as scikit-learn, XGBoost, LightGBM, CatBoost, spaCy, Optuna and a few more.
• The design and simplicity of PyCaret are inspired by the emerging role of citizen data scientists, a term first used by Gartner. Citizen Data Scientists are power users who can perform both simple and moderately sophisticated analytical tasks that would previously have required more technical expertise.

Documentations

• PyCaret Official Documentation

• Binary Classification Example

• Multiclass Classification Example

• Regression Example

• Time Series Forecasting Example

• Clustering Example

• Anomaly Detection Example