using CNN model stock price of itc predicted

1. ITC Stock Price Prediction
Report
Samarjit Sarkar

2. Content
 Problem Statement
 Strategy Adopted
 Reason of the Strategy
 Implementation
 Screenshots

3. Problem Statement
 ITC Stock Price Prediction Report

4. Strategy Adopted
 1D convolution followed by Max pooling Layer is used as a feature extraction and
then feed into Artificial neural Network and the prediction.
 Last 7 values of the close attribute is considered to predict the next close value.

5. Reason of the Strategy
 CNN is best for automatic feature extraction for Artificial Neural Network.
 After visualizing the correlation of the different attributes , considering only the last
7 days close value is enough to predict the next close value. So a 7X1 vector is
extracted from the dataset for the tanning and purpose.
Fig. 1 : Correlation of different attribute of Dataset

6. Implementation
 Model and Tanning: 1D CNN with Fully Connected Artificial Neural Network is
used. Architecture of the model is as follows-
 Input Shape : (7X1)
 1D Convolution Layer with 64 filters of kernel size is 3 and activation is ‘relu’
 1D MaxPooling Layer where pooling size is 2
 Flatten
 Dense Layer with 100 Neurons and activation is ‘relu’
 Dense Layer with 1 Neurons and activation is ‘linear’
 Loss : MSE , Metrics : MSE, Batch Size : 64 and Number of tanning Epoch is 5

7. Screenshot
Fig. 2. : Prediction VS Ground Truth in test dataset