Inspiration: To enhance customer insights by predicting future purchases using AI.
What it does: Predicts whether a participant will make a future purchase based on their data.
How I built it: Using Python, Scikit-learn, and RandomForestClassifier in Google Colab.
Challenges I ran into: Handling missing data, feature encoding, and ensuring consistent preprocessing.
Accomplishments that I'm proud of: Achieved high model accuracy (99.26%) and successfully automated predictions.
What I learned: Data preprocessing, feature engineering, model evaluation, and deployment techniques.
What's next for Predictionsss: Enhancing model performance, adding deep learning, and deploying as an API.
Built With
- collab
- python
- scikit-learn
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