Deep-Learning-Course/SecondSaturday/Workshop.md

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# 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.