Mobile Game Retention Forecasting: A Python Tutorial under 7 mins
🔗 Resources: https://github.com/a1441/RetentionCurve
Welcome to this in-depth tutorial on game retention forecasting using Python! 🎮🐍
In today's video, we'll walk you through:
Understanding Retention in Gaming: What it means and why it's vital for game developers and marketers.
Power Law Explained: Breaking down the power-law function, a mathematical model that helps us predict how many players keep coming back to a game.
Hands-On Coding Session: We'll write a Python script from scratch and dive deep into each line, ensuring you understand every step of the process. Perfect for both beginners and seasoned coders looking to sharpen their skills.
Visual Insights: Once our code is ready, we'll plot our results, helping you visualize player retention and forecast future trends.
Accuracy Matters: We'll also introduce a scoring system to measure the accuracy of our forecasts, ensuring your predictions are spot-on.
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0:00 Intro
0:37 Dependencies
0:52 Power Law
1:30 Inputs
1:27 Power Analysis
2:38 Parameter Estimation
3:02 Curve Fit
4:34 Forecast
5:26 Graph
5:40 Evaluation
5:52 Git and Final Words
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