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.