Update README.md

README.md

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 Purpose: Based on FinRL (https://github.com/AI4Finance-Foundation/FinRL), develop an AI stock-selection and trading strategy using Supervised Learning (SL) and Deep Reinforcement Learning (DRL), and deploy it to an online trading platform.
 
-### Phase I: Data Processing and Feature Engineering
-1. Download and install FinRL, download S&P 500 Open, High, Low, Close prices, and Volume (OHLCV) and Fundamental Indicators (company fundamental data), and convert the data into a daily format
+### Phase I: Financial Data Processing and Technical Indicators
 
-2. Perform feature engineering: based on OHLCV data to make company technical analysis indicators such as MACD, RSI; based on company fundamental data to make fundamental indicators such as EPS, ROI, ROE, P/E, P/S; and convert it into the specified data format
+1. Download Dow-30, NASDAQ-100, or S&P 500 data, including Open, High, Low, Close prices, and Volume (OHLCV) and fundamental indicators.
+
+2. Obtain technical indicators and perform feature engineering: technical indicators, such as MACD, RSI; and fundamental indicators, such as EPS, ROI, ROE, P/E, P/S.
 
 ### Phase II: Stock Selection and Portfolio Allocation with Backtesting Results
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 1. Stock Selection: Perform supervised machine learning using classic machine learning algorithms (LSTM, Random Forest, SVM, Linear Regression, Lasso, Ridge) to select stocks based on fundamental multi-factor data, and select the top 25% of stocks every quarter; 
 • Reference paper: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3302088
 • GitHub Code: https://github.com/AI4Finance-Foundation/Machine-Learning-for-Stock-Recommendation-IEEE-2018
@@ -18,8 +20,10 @@ Purpose: Based on FinRL (https://github.com/AI4Finance-Foundation/FinRL), develo
 • Reference paper: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3690996
 • GitHub Code: https://github.com/AI4Finance-Foundation/FinRL-Meta/blob/master/tutorials/1-Introduction/FinRL_PortfolioAllocation_NeurIPS_2020.ipynb
 
-### Phase III: Deploy the DRL trading strategy to an online trading platform
+### Phase III: Deploy a DRL agent to an online trading platform
+
 1. Deployment: Deploy strategies to online trading platforms such as Alpaca for paper trading
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 • GitHub Code: https://github.com/AI4Finance-Foundation/FinRL-Meta/blob/master/tutorials/3-Practical/FinRL_PaperTrading_Demo.ipynb