machine learning predict stock prices

培養皿. machine learning predict stock prices. 報告者：111319003 劉耿銘 108440050 江宏哲.

u. Outline. Preface Python syntax Development process Conclusion.

Preface. This project is expected to use python to predict the stock price. at present, this issue is quite hot all over the world, after all, it is most directly related to wealth. Many Investors Earn The Difference In The Price Of A Stock By Trading On An Online Trading Platform. Python Is A Very Popular Programming Language That Can Be Used To Solve A Variety Of Problems. It Has A Powerful Data Analysis Function That Can Be Used To Analyze Data From The Stock Market. As Far As The Industrial Structure Is Concerned, When We Find That Human Fund Managers Will Gradually Lose Their Jobs One Day In The Future, It May Mean That The A.I. Investment Forecasting Model At That Time Has Excellent And Stable Performance, And Can Completely Replace Humans..

Use Python libraries to get stock data yfinance Quandl Financial data processing tools Pandas SciPy NumPy.

1. 6 10.. Machine learning applied to stock price forecasting – a complete step-by-step flowchart To make an A.I. prediction model, the process is as follows: 1.Set forecast goals 2.Collect data 3.Select the A.I. model 4.Mark your prediction goals 5.Organize the rest of the information 6.Cut the material into learning, correction, and quizzes Let A.I. learning. Let A.I. make it right .Let the A.I. quiz 7Analysis of quiz results.

Step [1]: Set a forecast target. +11.4% -14.2% +10.9% i.

Step [2]: Collect data. Yahoo Finance: The main data source / US stock data is of good quality Python Modules Let's install the required modules first. pip install yfinance #Yahoo Finance python API pip install fredapi #FRED python API pip install pytrends #Google Trends python API.

Step [3]: Select the A.I. model. 一張含有 文字, 螢幕擷取畫面, 圖表, 軟體 的圖片 自動產生的描述.

Step [4~5]: Mark the prediction target and organize the remaining data.

Step 6: Divide the data into three parts. The first is Data Learning Xi Logic The second is a data-optimized AI model The third data test model performance.

步驟〔7〕 ：以AUC 分析. 一張含有 文字, 字型, 螢幕擷取畫面, 標誌 的圖片 自動產生的描述.

conclusion. Machine learning to predict stock prices by machines, which does not include human thoughts, news orientation, international economy, and any sudden environmental factors. Therefore, simply using machine learning to predict the stock market price can only make the simplest prediction, and the AI model of this project cannot provide effective prediction and implementation. This project can only machine learning the process and steps of how to develop a complete project in python, which can be of relative help if you want to study in this direction in the future..