Can AI Predict IMDb Ratings?
In this Python data analysis project, we explore an IMDb movies dataset containing more than 63,000 movies released between 1920 and 2026.
Starting with raw data, we clean and preprocess the dataset, perform exploratory data analysis (EDA), create insightful visualizations, and build a Random Forest Regressor to predict IMDb ratings using movie features such as duration, votes, and release year.
📌 In this video you'll learn:
Loading and exploring a real-world dataset with Pandas
Cleaning and preprocessing movie data
Feature engineering
Exploratory Data Analysis (EDA)
Data visualization with Matplotlib & Seaborn
Correlation analysis
Building a Machine Learning model
Evaluating model performance with MAE & R²
⏱️ Chapters
00:00 Intro
00:46 Load Data
01:11 Clean Data
06:20 Basic Info
07:16 Visualization
11:54 Machine Learning
13:58 Final Results
🛠️ Technologies Used
Python
Pandas
NumPy
Matplotlib
Seaborn
Scikit-Learn
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🔗 Code & dataset: https://www.kaggle.com/datasets/raeda...
🌐 Portfolio: https://ardaztt.github.io/my-data-por...
📩 Business: [email protected]
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