DA Mini project - Delhi house prediction session-2

In this video, we build a Python Mini Project on Delhi House Price Prediction using Machine Learning. You will learn how to analyze real-estate data, perform data preprocessing, and create a house price prediction model for Delhi using Python libraries.

This project demonstrates a complete end-to-end machine learning workflow, including data cleaning, exploratory data analysis (EDA), feature selection, model training, and evaluation. It is perfect for students, beginners, and aspiring data scientists looking to strengthen their Python and ML project skills.

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🔹 Libraries Used:
• NumPy
• Pandas
• Matplotlib & Seaborn
• Scikit-learn

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🔹 Topics Covered:
• Introduction to Delhi house price dataset
• Data cleaning & preprocessing
• Exploratory Data Analysis (EDA)
• Feature engineering
• Building house price prediction model
• Model evaluation & accuracy checking
• Real-world use case of machine learning

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🔹 Why This Project?

House price prediction is one of the most popular machine learning projects and a must-have for resumes, interviews, and academic submissions. This project helps you understand how regression algorithms are applied to solve real-world problems.

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🔹 Who Should Watch?
• Python beginners
• Data science & machine learning students
• Engineering & MBA analytics students
• Job & interview aspirants
• Anyone learning real-world ML projects

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