In this article we will understand Natural Language Inferencing and how it is a subset of Natural language processing.

This is my first case study, so you can expect a beginner-friendly data analysis and model building. I have used only the classical machine learning models for this problem. However, working on this case study was a great learning experience for me. And in this blog, I will try to share with you as much as possible. In the blog, I will write only the summary.

To train a robust machine learning model, one must select the correct machine learning algorithm with the correct combination of hyperparameters. The process of choosing the optimal set of parameters is known as hyperparameter tuning. One must train the dataset on all machine learning algorithms and on a different combination of its hyperparameters to improve the performance metric. The cross-validation technique can be used to train the dataset on various machine learning algorithms and choose the best out of it. Cross-Validation is a resampling technique that can be used to evaluate and select machine learning algorithms on a limited dataset.