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Predicting Product Purchase with K-Nearest Neighbors (KNN) Classifier

We will be using the Social network ad dataset The dataset contains the details of users in a social networking site to find whether a user buys a product by clicking the ad on the site based on their salary, age, and gender. Step 1: Import Libraries Let’s start by importing essential libraries: Step 2: […]

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 […]

Distributed Query Execution

In today’s data-centric world, distributed query execution is essential for efficiently managing and analyzing large-scale datasets spread across multiple systems. This blog provides an overview of distributed queries, explains their workings, and offers practical tips for optimizing their performance. What is a Distributed Query? A distributed query refers to a query that retrieves or processes […]

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 […]

Terraform Essentials: When to Use terraform refresh vs terraform plan

When working with Terraform, two commonly used commands are terraform refresh and terraform plan. While both involve examining the state of your infrastructure, they serve distinct purposes. What is terraform refresh? The terraform refresh command updates the Terraform state file with the current state of your real-world infrastructure. Key Points: Example: Suppose you manually change […]

Revolutionizing Data Handling: How AI Transforms Query Optimization Across Industries

The practical impact of AI-driven query optimization can be seen across various industries, revolutionizing how businesses operate and innovate. From streamlining e-commerce searches to accelerating healthcare research and enhancing financial fraud detection, AI is making databases more efficient and intelligent. Below are some specific examples of how AI is being applied to solve real-world data […]

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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