Update README.md

README.md

@@ -1,3 +1,23 @@
+---
+license: apache-2.0
+datasets:
+- dirganmdcp/yfinance_Indonesia_Stock_Exchange
+language:
+- en
+metrics:
+- mape
+pipeline_tag: time-series-forecasting
+library_name: keras
+tags:
+- time-series
+- stock-forecasting
+- LSTM
+- ARIMA
+- Prophet
+- machine-learning
+- deep-learning
+- forecasting
+---
 # 📈 Stock Price Forecasting - DataSynthis ML Job Task
 
 This repository contains implementations of **time-series forecasting** for stock prices using both **traditional statistical models (ARIMA, Prophet)** and **deep learning (LSTM)**.  
@@ -57,5 +77,4 @@ The performance of the three models on stock price forecasting is summarized bel
 - **LSTM** achieved the **lowest RMSE and MAPE**, showing the best accuracy.  
 - **ARIMA** performed reasonably well, but less effective with non-linear trends.  
 - **Prophet** captured trends and seasonality but had higher errors.  
-- Overall, **LSTM is the most reliable model** for this task.
-
+- Overall, **LSTM is the most reliable model** for this task.