Skip to content

Our goal in this project is to use Long Short-Term Memory (LSTM) to predict the future stock prices of the AI company.

Notifications You must be signed in to change notification settings

MichaelFish199/Ai-Stock-Forecast-Using-LSTMs

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

2 Commits
 
 
 
 

Repository files navigation

Welcome to my notebook on AI Stock Forecast 📈 Using LSTMs! In this project, we will be using a dataset called C3.AI Stocks Dataset, which is a collection of stock market data sourced from Yahoo for the period from March 2022 to March 2023. This dataset contains several columns of data for each stock, including the date on which the stock market data was recorded, the opening price of the stock, the highest and lowest prices of the stock on a given day, the closing price of the stock, the adjusted closing price that accounts for any corporate actions that may have affected the stock's price, and the total number of shares traded in the stock on a given day.

Our goal in this project is to use Long Short-Term Memory (LSTM) neural networks, a type of Recurrent Neural Networks (RNN), to predict the future stock prices of the AI company. LSTM networks are a powerful type of neural networks that can capture long-term dependencies in time-series data, making them ideal for stock price prediction tasks.

About

Our goal in this project is to use Long Short-Term Memory (LSTM) to predict the future stock prices of the AI company.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published