• Hidden Markov Model
• Word2Vec
• Neural Temporal Point Processes
• Hate speech detection
• Toxic speech classification

Implemented Hidden Markov Model (HMM) to generate and classify reviews

Implemented Word2Vec to obtain word embeddings

Implemented Neural Temporal Point Processes to model the time of occurrence of events

Implemented a Fully Connected Neural Network to detect hate speech in tweets.

• Tweets labels: RACIST, SEXIST, NEITHER

• Data Preprocessing

  • LabelEncoder for labels
  • Universal Sentence Encoder to get text embeddings

Employed DistilBERT to classify tweets to detec toxic speech.

• Tweets labels: none, racism, sexism

• Data Preprocessing

  • LabelEncoder for labels
  • BertTokenizer to get text tokens
  • padding
  • CustomDataset
  • Split to Train/Val/Test 60/20/20

• Model: DistilBERT

• Explanation using SHAP