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Welcome to HCL GUVI

Hey there! Welcome to HCL GUVI—Grab Your Vernacular Imprint—where tech learning is easy, fun, and curated specially for you. Incubated by IIT Madras & IIM Ahmedabad in 2014 and now part of HCL Group, we're making quality tech education accessible to all.

Join 3M+ learners breaking barriers and upskilling for a brighter future. We're here to guide you every step of the way! 🚀

LIVE Classes

Zen Classes are HCL GUVI's most refined and flagship product—live, expert-led tech programs for beginners and pros. With IITM Pravartak affiliations, master Full-Stack, Data Science, DevOps, UI/UX, and more in multiple languages!

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Practice Platforms

Enhance your coding skills with HCL GUVI's Practice Platforms—interactive, structured, and designed to help you master programming effortlessly.

CodeKata:

A structured coding practice platform with 1500+ coding problems designed by industry experts. Ideal for beginners and professionals preparing for tech interviews with real-world coding challenges.

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WebKata:

An interactive platform to master HTML, CSS, JavaScript, and Bootstrap with a live coding environment. Perfect for hands-on web development practice without any setup.

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SQLKata:

A practice ground for mastering SQL queries used in real-world applications. Write, optimize, and refine your queries to build strong database skills.

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FixTheCode:

Hone your bug-fixing skills with real-world debugging challenges in Python, C++, JavaScript, and Golang. More languages coming soon!

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IDE:

A free online compiler supporting 20+ programming languages with auto-complete, debugging, and AI-powered code generation—all in the cloud!

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Home
Python 3
Project Workflow

Fake Review Detection Project Workflow Explained

Workflow Diagram
Project Pipeline

Project Workflow

Workflow Diagram

Collect Dataset

↓

Load Dataset

↓

Explore Dataset

↓

Clean Text Data

↓

Preprocess Reviews

↓

Convert Text to Numerical Features

↓

Train Machine Learning Model

↓

Evaluate Performance

↓

Predict New Reviews

Project Pipeline

Step 1

Load the dataset.

Step 2

Explore the available columns.

Step 3

Clean and preprocess review text.

Step 4

Convert text into numerical vectors using TF-IDF.

Step 5

Split the dataset into training and testing sets.

Step 6

Train a Logistic Regression classifier.

Step 7

Evaluate the model using classification metrics.

Step 8

Predict whether unseen reviews are fake or real.

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Fake Review Detection Project Workflow Explained

Contents

Project Workflow

Workflow Diagram

Project Pipeline

Step 1

Step 2

Step 3

Step 4

Step 5

Step 6

Step 7

Step 8

Fake Review Detection System using Machine Learning

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