Menu
Menu

    LIVE Classes

    VLSI Design Programme
    VLSI Design Programme New

    IIT Delhi certified

    AI & Machine Learning
    AI & Machine Learning New

    Intel & IIT-M Pravartak certified

    Data Science
    Data Science

    IIT-M Pravartak certified

    Full Stack Development
    Full Stack Development

    IIT-M Pravartak certified

    UI/UX Design
    UI/UX Design

    HCL GUVI certified

    AI DevOps Program
    AI DevOps Program

    HCL GUVI certified

    Courses

    Free Courses

    Free Courses

    Paid Courses

    Paid Courses

    Combo Courses

    Combo Courses

    Practice

    CodeKata

    CodeKata

    Sharpen your coding skills, prepare for interviews

    WebKata

    WebKata

    Build basic frontend & backend development skills

    SQLKata

    SQLKata

    Master SQL concepts in relational database management

    FixTheCode

    FixTheCode

    A series of programs curated by industry experts

    IDE - Online Compiler

    IDE - Online Compiler

    Run & test your code in any programming language

    Resources

    Free Resources

    Free Resources

    Referral

    Referral

    Success Stories

    Success Stories

    Blogs

    Blogs

    Learn Hub

    Learn Hub

    Get The App

    Get The App

    Rewards

    Rewards

    Become an Affiliate

    Become an Affiliate

    Leaderboard

    Leaderboard

    What's New?
    Resume Builder

    Resume Builder

    Our Products

    HackerKID

    HackerKID

    Coding classes platform for K-12 children

    GUVI For Corporates

    GUVI For Corporates

    Meet your Hiring & Training Needs

    Placement Preparation

    Placement Preparation

    Ace Up your Aptitude

    Play StoreApp Store
Still Confused?WhatsApp

Welcome to HCL GUVI

Welcome Img

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

Live Class Img

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!

Explore More

Courses

Courses Img

Looking for flexibility? HCL GUVI's 200+ self-paced courses let you learn anytime, anywhere! From free lessons to IIT-M & Autodesk-certified programs, gain in-demand skills in your preferred language.

Explore More

Practice Platforms

Practice Platform Img

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.

Try Now >

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.

Try Now >

SQLKata:

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

Try Now >

FixTheCode:

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

Try Now >

IDE:

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

Try Now >

Leaderboard

LeaderBoard Img

Climb the leaderboard as you earn Geekoins by learning and practicing! The top scorers get featured, making learning competitive and rewarding. Keep going—you could be next!

Explore More

Rewards

Rewards Img

Earn Geekoins by watching videos and practicing problems, then redeem them for exciting rewards. The more you engage, the more you win!

Explore More

Referral

Referral Img

Love learning with HCL GUVI? Share it with friends! Invite them using your unique link or code and unlock exciting rewards—Amazon vouchers, iPhones, and more. A Win-Win.

Explore More

Profile

Profile Img

Your HCL GUVI profile is your digital portfolio! Track progress, showcase skills, add projects, and build a resume. Keep it updated—opportunities await!

Explore More

That's It! You Are Ready!

Finish Img

You're all set to dive into your learning journey with HCL GUVI. Explore, upskill, and make each step count—exciting possibilities awaits!

Thank you for Reaching us out

Our team will reach you out
within the next 24 hours.

Explore all Programs

Making Predictions Using the Trained Model

Making Predictions Using the Trained Model

After training, the model is ready to predict house prices.

The first step is generating predictions on the training dataset.

Code

**y_train_pred = model.predict(X_train)**

**print(len(y_train_pred))**

Explanation

The predict() function uses the trained XGBoost model to estimate house prices based on the input features.

The output contains predicted prices for every record in the training dataset.

At this stage, we can compare these predictions with the actual house prices to measure performance.

Share

You can share this topic with your family and friends on Social Media.

Share in

House Price Prediction Using Machine Learning (XGBoost)

VA
Vishalini A

House Price Prediction Using Machine Learning (XGBoost)

MODULE 1 : Introduction
lessonIntroduction of the Project
lessonWhat Is Data Science? Key Concepts and Core Features
lessonWhat Is Machine Learning?
lessonUnderstanding Regression Problems
lessonUnderstanding the House Price Prediction Problem
lessonUnderstanding the California Housing Dataset
lessonAim of the Project
MODULE 2 : Environment Setup and Exploratory Data Analysis
lessonEnvironment Setup and Exploratory Data Analysis
lessonWhy Use Google Colab?
lessonImporting Required Libraries
lessonLoading the California Housing Dataset
lessonCreating a Pandas DataFrame
lessonInspecting the Dataset
lessonUnderstanding Dataset Dimensions
lessonChecking for Missing Values
lessonStatistical Summary of the Dataset
lessonIntroduction to Exploratory Data Analysis
lessonUnderstanding Correlation
lessonCreating a Correlation Matrix
lessonVisualizing Correlations Using a Heatmap
MODULE 3 : Preparing Data for Machine Learning
lessonPreparing Data for Machine Learning
lessonWhy Data Preparation Matters
lessonUnderstanding Features and Labels
lessonSeparating Features and Target Variables
lessonUnderstanding Train-Test Split
lessonWhy We Need Unseen Data
lessonSplitting the Dataset
lessonCreating Training and Testing Sets
lessonUnderstanding the Resulting Datasets
lessonInspecting Training Data
lessonInspecting Testing Data
lessonUnderstanding Data Leakage
lessonPreparing for Model Training
MODULE 4 : Building the House Price Prediction Model Using XGBoost
lessonBuilding the House Price Prediction Model Using XGBoost
lessonWhat Is XGBoost?
lessonUnderstanding Ensemble Learning
lessonUnderstanding Decision Trees
lessonUnderstanding Gradient Boosting
lessonImporting the XGBoost Regressor
lessonCreating the Model
lessonTraining the Model
lessonHow the Model Learns
lessonUnderstanding Model Parameters
lessonWhy XGBoost Is Effective for House Price Prediction
lessonTraining Completion
MODULE 5 : Model Evaluation and Prediction
lessonModel Evaluation and Prediction
lessonMaking Predictions Using the Trained Model
lessonUnderstanding Regression Evaluation Metrics
lessonUnderstanding R square Score
lessonUnderstanding Mean Absolute Error (MAE)
lessonWhy Training Performance Alone Is Not Enough
lessonEvaluating the Model on Test Data
lessonCalculating Test R square Score
lessonUnderstanding Generalization
lessonVisualizing Actual vs Predicted Prices
MODULE 6 : Project Conclusion
lessonProject Conclusion
lessonLive Link and Output Overview
lessonMCQs
lessonResources

House Price Prediction Using Machine Learning (XGBoost)

MODULE 1 : Introduction
lessonIntroduction of the Project
lessonWhat Is Data Science? Key Concepts and Core Features
lessonWhat Is Machine Learning?
lessonUnderstanding Regression Problems
lessonUnderstanding the House Price Prediction Problem
lessonUnderstanding the California Housing Dataset
lessonAim of the Project
MODULE 2 : Environment Setup and Exploratory Data Analysis
lessonEnvironment Setup and Exploratory Data Analysis
lessonWhy Use Google Colab?
lessonImporting Required Libraries
lessonLoading the California Housing Dataset
lessonCreating a Pandas DataFrame
lessonInspecting the Dataset
lessonUnderstanding Dataset Dimensions
lessonChecking for Missing Values
lessonStatistical Summary of the Dataset
lessonIntroduction to Exploratory Data Analysis
lessonUnderstanding Correlation
lessonCreating a Correlation Matrix
lessonVisualizing Correlations Using a Heatmap
MODULE 3 : Preparing Data for Machine Learning
lessonPreparing Data for Machine Learning
lessonWhy Data Preparation Matters
lessonUnderstanding Features and Labels
lessonSeparating Features and Target Variables
lessonUnderstanding Train-Test Split
lessonWhy We Need Unseen Data
lessonSplitting the Dataset
lessonCreating Training and Testing Sets
lessonUnderstanding the Resulting Datasets
lessonInspecting Training Data
lessonInspecting Testing Data
lessonUnderstanding Data Leakage
lessonPreparing for Model Training
MODULE 4 : Building the House Price Prediction Model Using XGBoost
lessonBuilding the House Price Prediction Model Using XGBoost
lessonWhat Is XGBoost?
lessonUnderstanding Ensemble Learning
lessonUnderstanding Decision Trees
lessonUnderstanding Gradient Boosting
lessonImporting the XGBoost Regressor
lessonCreating the Model
lessonTraining the Model
lessonHow the Model Learns
lessonUnderstanding Model Parameters
lessonWhy XGBoost Is Effective for House Price Prediction
lessonTraining Completion
MODULE 5 : Model Evaluation and Prediction
lessonModel Evaluation and Prediction
lessonMaking Predictions Using the Trained Model
lessonUnderstanding Regression Evaluation Metrics
lessonUnderstanding R square Score
lessonUnderstanding Mean Absolute Error (MAE)
lessonWhy Training Performance Alone Is Not Enough
lessonEvaluating the Model on Test Data
lessonCalculating Test R square Score
lessonUnderstanding Generalization
lessonVisualizing Actual vs Predicted Prices
MODULE 6 : Project Conclusion
lessonProject Conclusion
lessonLive Link and Output Overview
lessonMCQs
lessonResources

ZEN CLASS

LIVE CLASS

Popular Courses

Self-Paced Courses

Practice Platforms

Community

Products

Resources

Company

ZEN CLASS

LIVE CLASS

Popular Courses

Self-Paced Courses

Practice Platforms

Community

Products

Resources

Company

app store
play store
Refer & Earn

HCL GUVI (Grab Your Vernacular Imprint) Geek Network Private Limited is a leading online learning and skills development company, incubated by IIT Madras and IIM Ahmedabad.

Established in 2014 and acquired by the HCL Group in 2022, HCL GUVI is dedicated to providing effective and high-quality learning and skilling programs that transcend language barriers in technology education. HCL GUVI today is trusted by over 4.8 million users, 20 languages and 2500+ corporate partners.

app storeplay store
Refer & Earn

HCL GUVI (Grab Your Vernacular Imprint) Geek Network Private Limited is a leading online learning and skills development company, incubated by IIT Madras and IIM Ahmedabad.

Established in 2014 and acquired by the HCL Group in 2022, HCL GUVI is dedicated to providing effective and high-quality learning and skilling programs that transcend language barriers in technology education. HCL GUVI today is trusted by over 4.8 million users, 20 languages and 2500+ corporate partners.

app storeplay storeRefer & Earn
Terms and ConditionsPrivacy Policy

HCL GUVI Geek Network Pvt. Ltd.

Terms and ConditionsPrivacy Policy

HCL GUVI Geek Network Pvt. Ltd.