📈 Pushed SARIMA model and card for SAP SE

README.md

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+---
+title: TurnoverForecasting
+emoji: 📊
+colorFrom: blue
+colorTo: red
+sdk: gradio
+sdk_version: 5.22.0
+app_file: app.py
+pinned: false
+license: mit
+short_description: Forecasting SAP SE Revenue with AI
+---
+
+# 📊 AI-Powered Turnover Forecasting for SAP SE
+
+## 🚀 Project Overview
+
+This project delivers **AI-driven revenue forecasting** for **SAP SE** using a **univariate SARIMA model**.
+It shows how accurate forecasts can be built from limited data (just historical turnover).
+
+---
+
+## 🏢 Why SAP SE?
+
+- SAP SE is a **global leader in enterprise software**
+- Revenue forecasts support **strategic planning & growth**
+- Perfect case for **AI-powered financial forecasting**
+
+---
+
+## 🧠 Model Details
+
+- **Model type**: SARIMA (Seasonal ARIMA)
+- **Trained on**: SAP SE revenue from Top 12 German Companies Dataset (Kaggle)
+- **SARIMA Order**: (3, 1, 5)
+- **Seasonal Order**: (0, 1, 0, 12)
+- **Evaluation Metric**: MAE (Mean Absolute Error)
+- **Validation**: Walk-forward validation with test set (last 10%)
+
+---
+
+## ⚙️ How to Use
+
+```python
+import pickle
+
+with open("sarima_sap_model.pkl", "rb") as f:
+    model = pickle.load(f)
+
+forecast = model.forecast(steps=4)
+print(forecast)
+```
+
+## 📌 Intended Use & Limitations
+✅ Forecast SAP SE revenue for next 1–6 quarters  
+📈 Great for univariate, seasonal time series  
+🚫 Not suitable for multivariate or non-seasonal data  
+⚠️ Requires careful preprocessing (e.g., stationarity)
+
+👨‍💻 Author: Pranav Sharma

config.json

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+{
+    "sklearn": {
+        "columns": [
+            "Period",
+            "Company",
+            "Revenue",
+            "Net Income",
+            "Liabilities",
+            "Assets",
+            "Equity",
+            "ROA (%)",
+            "ROE (%)",
+            "Debt to Equity"
+        ],
+        "environment": [
+            "pandas",
+            "statsmodels",
+            "scikit-learn"
+        ],
+        "example_input": {
+            "Assets": [
+                65782612977,
+                23437806831,
+                55383211771
+            ],
+            "Company": [
+                "SAP SE",
+                "SAP SE",
+                "SAP SE"
+            ],
+            "Debt to Equity": [
+                0.393327841,
+                0.930170072,
+                2.717704304
+            ],
+            "Equity": [
+                47212587750,
+                12142871334,
+                14897153522
+            ],
+            "Liabilities": [
+                18570025227,
+                11294935497,
+                40486058249
+            ],
+            "Net Income": [
+                719090971.2,
+                744873003.7,
+                1997618536.0
+            ],
+            "Period": [
+                "2017-03-31",
+                "2017-06-30",
+                "2017-09-30"
+            ],
+            "ROA (%)": [
+                1.093132271,
+                3.17808321,
+                3.606902655
+            ],
+            "ROE (%)": [
+                1.523091628,
+                6.134241097,
+                13.40939753
+            ],
+            "Revenue": [
+                6568715630,
+                6644029236,
+                18227487487
+            ]
+        },
+        "model": {
+            "file": "sarima_sap_model.pkl"
+        },
+        "model_format": "pickle",
+        "task": "tabular-regression"
+    }
+}

sarima_sap_model.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:f342e2356bfffc11f45e62ce62b3de32c257f41330eccd4e06871cc84b1f9cdb
+size 2088916