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README.md

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+
+---
+tags:
+- time-series
+- regression
+- svr
+- stock-prediction
+- scikit-learn
+---
+# SVR Model for AAPL Price Prediction
+
+This repository hosts a trained **Support Vector Regression (SVR)** model and its necessary preprocessing components (MinMaxScaler) for predicting the closing price of **AAPL**.
+
+## Model Details
+- **Algorithm:** Support Vector Regression (SVR) with RBF Kernel
+- **Features (Input Sequence Length):** 60 days
+- **Target:** Single-step prediction (the price of day $T+1$)
+- **Training Period:** 2020-11-24 to 2025-11-23
+
+## Inference
+To use this model, you must provide a sequence of the last **60** scaled closing prices.
+
+1.  Load the `svr_model.joblib` and `minmax_scaler.joblib`.
+2.  Scale your 60-day input sequence using the loaded `MinMaxScaler`.
+3.  Run the prediction.
+4.  Inverse transform the prediction using the loaded `MinMaxScaler` to get the final dollar value.
+