As deployer/Maintainer I should be able to improve Handwritten Block letter Alphanumeric model Accuracy by experimenting with open and synthetic datasets - Iteration 2

[dileep-gadiraju]

As deployer/Maintainer I should be able to improve the Handwritten Block letter Alphanumeric model Accuracy by experimenting with open and synthetic datasets - Iteration 2.
Note: Expected accuracy improvement is approximately 3% to 5%.

• Experiment with the existing model version (https://github.com/Sunbird-Saral/Project-Saral/tree/main/v1.0/frontend/SaralApp/android/saralsdk/src/main/assets#:~:text=model_letter_digits_finetune_18_07_22_epoch_15.tflite) to identify the miss-classifications.
• Identifying open data sets
• Experiment by inferencing the existing model with the new dataset and check the results and Prepare the new data
  Training the next version of the model.
• Inferencing and identifying optimal model version/checkpoint.
• Package with SaralSDK/SaralReference App to test in real-time.