S&P Stock Index Prediction

Oveview

This project was done as a part of “Artificial Intelligence” course during my B.Sc. period. It aims to predict S&P stock index using Deep Learning approach. Feedforward Neural Network is used.

Architecture of the Network — Architecture of the network used

Results

At the end of the 10th epoch, the MSE on the test data is 0.00078 and the error is 5.13%.

Languages/Technologies Used

Technology	Usage
	Python language is used for developing the applications
	Tensorflow is the framework for developing machine learning applications
	Git is used for the version control

Project information

Category: AI
Client: AI Course
Project date: Fall 2017
Project URL: http://www.boute.ir/iust-ai-96/stock-prediction
Github Repository: https://github.com/abradat/stock-prediction

Project Description
S&P Stocker Index Prediction using Feed Forward Neural Networks implemented in Tensorflow.