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Author : Mausomi Paul

Installing Minikube

Prerequisites 1. Before installing the minikube it is recommended to install all available updates on your system. 2. Minikube requires either docker or Virtualbox, in this article we will be installing docker on Ubuntu. You can also refer to the official website for installing docker or you can follow the below post. 3. Install the […]

How Selenium Handle Alerts and Pop-ups

In this article, we explored how to handle different types of JavaScript popups — alerts, confirm boxes, and prompt boxes — using Selenium. Each popup requires immediate user interaction and can be managed with driver.switch_to.alert. We used methods like accept(), dismiss(), and send_keys() to interact with these dialogs. Alerts and Popups Demo Alerts and Popups […]

Text Preprocessing: Lemmatization and Stop-words

In this article, you will learn about the lemmatization and stop-words which are a part of a text preprocessing. Lemmatization is the process of reducing words to their base or dictionary form, known as the lemma. Implementation of Lemmatization import nltkfrom nltk.stem import WordNetLemmatizer The WordNetLemmatizer is part of the Natural Language Toolkit (NLTK) library and […]

Stemming Techniques using NLTK Library

This article focuses on understanding and applying different stemming techniques used in Natural Language Processing (NLP) to reduce words to their root forms. Stemming is an essential preprocessing step that simplifies text data, helping in tasks like text analysis, classification, and search optimization. Stemming is the process of reducing a word to its linguistic root. […]

Exploring Different Tokenization Techniques in NLP using NLTK Library

In this article, you will explore various tokenization methods provided by the Natural Language Toolkit (NLTK) to process and analyse textual data. Tokenization is a crucial preprocessing step in Natural Language Processing (NLP), where text is broken down into smaller units, such as sentences or words. Tasks 1. Open a notebook a jupyter. 2. Start […]

Streamlit-Based Machine Learning Model for Iris Flower Dataset

In this activity, you will build an interactive web application for classifying Iris flower species using Streamlit and a Random Forest Classifier algorithm. This practical is a hands-on demonstration of combining machine learning and web application development to create a user-friendly tool for predictive analysis. Streamlit is an open-source Python framework for data scientists and AI/ML […]

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