Stock Price Prediction
Introduction
The stock market has always played a huge role in the global economy. That is why it will be meaningful to see how artificial intelligence can be applied in stock price prediction. As beginners to AI, this was an excellent project to start with. For AI projects, data is integral to its success and often it could be hard to obtain reliable data. However, the stock market has many different datasets that are readily available. Both from an interest and practicality perspective, stock price prediction was a great project for us who want to learn more about applications of AI in the real world.
Goals
- Learn the basics of artificial intelligence and machine learning
- Apply this knowledge to the stock price prediction project using online articles as aid
- Have fun learning some new and interesting
Learnings and Tutorials
- Machine Learning by Stanford University
- Neural Networks and Deep Learning
- Predicting Stock Trend Using Deep Learning
Methodologies and Tools
- Dataset: NSE Tata Global stock, Apple stock
- Recurrent Neural Network (RNN)
- Pandas: preprocessing
- Keras: LSTM, Adam optimizer
Result
The model is quite accurate in the beginning but the accuracy decreases as time increases
