Table of Contents

1. Import of Data Sets

2. Pre-processing of Data Sets

   1. Detection and Removal of Empty data
      
   2. Plotting and Analysis of Data
      
   3. Outlier detection and Removal
      
   4. Visualizing Outlier removed Data set
      

3. Data preparation for LSTM model 1

   1. Array initialization, dropping, Reshaping
   2. Splitting of Data set for Training and Testing

4. LSTM Model 1

   1. Model Design
   2. Setting Callbacks
   3. Training and Validation of the Model
   4. Plot of the Loss and Value Loss vs Epoch

5. Predicting Values from LSTM 1

6. Data preparation for LSTM model 2 (Work in Progress)

7. LSTM Model 2 (Work in Progress)

8. Predicting values from LSTM model 2 (Work in Progress)

9. Analysis and Comparison (Work in Progress)