gghati/Emojifier

This is a NLP project to Predict the Emojis for the Given Text, Using LSTM Structure.

Emojifier!

Have you ever wanted to make your text messages more expressive? Your emojifier app will help you do that. So rather than writing:

"Congratulations on the promotion! Let's get coffee and talk. Love you!"

The emojifier can automatically turn this into:

"Congratulations on the promotion! 👍 Let's get coffee and talk. ☕️ Love you! ❤️"

This is a NLP project to Predict the Emojis for the Given Text, Using LSTM Structure.

Baseline model: Emojifier

About Dataset emojiset

The dataset (X, Y) where:

• X contains 127 sentences (strings).
• Y contains an integer label between 0 and 4 corresponding to an emoji for each sentence.
• as shown in the below picture.

EMOJISET - a classification problem with 5 classes. A few examples of sentences are given here.

Inputs and outputs to the embedding layer

• The figure shows the propagation of two example sentences through the embedding layer.
  • Both examples have been zero-padded to a length of max_len=5.

Embedding layer

Overview of the LSTM model

This is the LSMT structure that we're going use for prediction:

Emojifier. A 2-layer LSTM sequence classifier.

Output Accuracy :

Trainset Accuracy of the Emoji Predicted Model.

Output of the Model:

Output of the Model on given String!

This Project is inspired by the Coursera's course on Sequence Models!