Deep-Learning-Course/SecondSaturday/Workshop.md

# swipe input keyboard for indian languages.
given a gesture made on the keybard,language chosen-> keyboard layout
predict the word that matches closest.


## Input
gesture data -> polygon(shape,size,corners, path), (time, pauses)?, spatial data with word character correlation.
weighted-vocabulary,corpus for the language,history of gesture-word mappings/corrections for the user.
language, keyboard layout

## Output
  Predict the word

## Model
  Structured Output/HMM/CNN?

# mnist hand-written digit database -> build application for recognizing full phone numbers(10 digit).

## Input
mnist digit database, generated 10 digit images with random positioning,orientation,scale of individual digit images sampled randomly from the mnist database.

## Output
  predict the phone number

## Model
  regression model to identify the points where the split for the images has to be made and pass the
  split images to mnist digit recognizer to identify the digit.