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Fake Review Detection System using Machine Learning

Fake Review Detection System using Machine Learning

The Fake Review Detection System Using Machine Learning project is a beginner-friendly Machine Learning project that demonstrates how to build a text classification system using the Fake Reviews Dataset. Learners will preprocess customer reviews, apply TF-IDF Vectorization, train a Logistic Regression classifier, evaluate the model using multiple performance metrics, and predict whether reviews are fake or genuine using Python and Scikit-learn.

8 Modules

48 Lessons

English

1 Hr

Reading Plan

MODULE 1

Project Introduction

3 mins

Project Overview

1 min

Applications of Fake Review Detection

1 min

Project Workflow

1 min

MODULE 2

Setting Up Google Colab

4 mins

Importing Required Libraries

1 min

Uploading the Dataset

1 min

Loading the Dataset

1 min

Understanding the Dataset

1 min

MODULE 3

Data Cleaning and Text Preprocessing

7 mins

Checking for Missing Values

1 min

Checking for Duplicate Reviews

1 min

Understanding the Target Labels

1 min

Cleaning Review Text

1 min

Removing Stopwords

1 min

Lemmatization

1 min

Comparing Original and Cleaned Reviews

1 min

MODULE 4

Exploratory Data Analysis (EDA)

8 mins

Understanding the Distribution of Reviews

1 min

Review Length Analysis

1 min

Statistical Summary of Review Length

1 min

Most Common Words in Reviews

1 min

Visualizing the Most Common Words

1 min

Creating a Word Cloud

1 min

Fake vs Genuine Review Distribution

1 min

Correlation Analysis (Numerical Features)

1 min

MODULE 5

Feature Engineering

6 mins

Why Text Needs to Be Converted into Numbers

1 min

Converting Reviews into TF-IDF Features

1 min

Preparing the Target Variable

1 min

Splitting the Dataset

1 min

Understanding the Training and Testing Data

1 min

Visualizing the Class Distribution in the Training Set

1 min

MODULE 6

Building the Machine Learning Model

8 mins

Introduction to Logistic Regression

1 min

Training the Logistic Regression Model

1 min

Making Predictions

1 min

Calculating Model Accuracy

1 min

Visualizing the Accuracy

1 min

Predicting a Single Review

1 min

Testing Multiple Reviews

1 min

Saving the Trained Model

1 min

MODULE 7

Model Evaluation

8 mins

Introduction to Model Evaluation

1 min

Confusion Matrix

1 min

Classification Report

1 min

Calculating Precision, Recall, and F1-Score

1 min

Comparing Evaluation Metrics

1 min

ROC Curve

1 min

Calculating the AUC Score

1 min

Feature Importance

1 min

MODULE 8

Project Results and Final Evaluation

4 mins

Project Results and Final Evaluation

1 min

Live Output and Prediction Overview

1 min

Multiple Choice Questions (MCQs)

1 min

Resources

1 min

Contributors

Vishalini A

Fake Review Detection System using Machine Learning

Learn how to build a Fake Review Detection System using Python and Machine Learning. This beginner-friendly handbook covers text preprocessing, TF-IDF Vectorization, Logistic Regression, model evaluation, and fake review classification using the Fake Reviews Dataset.

Fake Review Detection System Using Machine Learning – AI-Based Review Classification Project

This handbook provides hands-on experience in building a Fake Review Detection System using Python and Machine Learning. Learners will preprocess review text, apply TF-IDF vectorization, train a Logistic Regression model, evaluate it using classification metrics, and predict whether reviews are fake or genuine. The project offers practical experience in Natural Language Processing, feature engineering, text classification, and machine learning.

Fake Review Detection System Using Machine Learning – AI-Based Review Classification Project

Prerequisites

This course is suitable for:

Basic knowledge of Python programming
Understanding of Data Science fundamentals
Familiarity with Machine Learning concepts
Basic understanding of Natural Language Processing (NLP)
Basic knowledge of text classification algorithms
A Google account to access Google Colab
A Kaggle account to download the Fake Reviews Dataset
Internet connection to access datasets and required Python libraries

Run & Test your Code with our very own IDE that supports 16 languages

Open IDE

8 Modules

48 Lessons

English

1 Hr

Contributors

Vishalini A

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