Beginner’s Guide To Text Classification Using PyCaret
Introduction
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.
ML Pipeline/ ML Cycle (Credits: https://medium.com/analytics-vidhya/machine-learning-development-life-cycle-dfe88c44222e)
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:
The process of solving a machine learning problem involves a lot of time and human