dg492003/tradeaialytics

This web application, developed using Dash (a Python framework) and machine learning models, allows users to input a stock code. Based on this code, the application fetches and displays stock plots. The machine learning component predicts stock prices for a specific date provided by the user.

TradeAIalytics

This web application, developed using Dash (a Python framework) and machine learning models, allows users to input a stock code. Based on this code, the application fetches and displays stock plots. The machine learning component predicts stock prices for a specific date provided by the user.

• index_app.py contains web layout and server function. We will be referring to it as our main file.
• model.py is where we will implement a machine learning model for forecasting the stock price.
• style.css is the css file for styling the web app.
• requirements.txt is correct versions of the required Python packages to run the Python code.

Screenshots

• Interface of a Website

• Inputting a stock code
  

• Inputting a start-date and end-date

• Getting Moving Average by clicking Indicator button

• Applying model.py
  

🛠 Skills

Python, Dash, HTML, CSS, Scikit-learn, pandas.....

API Reference

Get all items

Here we use Financialmodelprep api to fetch the all data

Parameter	Type	Description
api_key	string	Required. Your API key