README.md

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!