Beginner’s Guide To Text Classification Using PyCaret


Have you ever solved a Machine Learning problem in just one go?

Solving a problem using machine learning isn’t straightforward. It involves various steps to come up with an accurate solution. The process/steps to be followed for solving an ml problem is known as ML Pipeline/ML Cycle.

As shown in the figure, the Machine Learning pipeline consists of different steps like:

Understand Problem Statement, Hypothesis Generation, Exploratory Data Analysis, Data Preprocessing, Feature Engineering, Feature Selection, Model Building, Model Tuning, and Model Deployment.

I would recommend going through the below articles for in detailed understanding of the Machine Learning pipeline:

  1. Machine Learning Life-cycle Explained!
  2. Steps to Complete a Machine Learning Project

The process of solving a machine learning problem involves a lot of time and human




To finish reading, please visit source site