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# ------------------------------------------------- # 2. Scale data to [0,1] # ------------------------------------------------- scaler = MinMaxScaler() scaled = scaler.fit_transform(df[['count']])

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# ------------------------------------------------- # 6. Real‑time inference (example) # ------------------------------------------------- def predict_next(current_window): """current_window: np.array shape (look_back, 1) already scaled""" pred_scaled = model.predict(tf.expand_dims(current_window, axis # ------------------------------------------------- # 2