Syllabus

  • What is NLP, NLU and NLG
  • What is the need of NLP?
  • What is a real life application of NLP?
  • Different type of Data
  • Web Scraping - Wikipedia, Google news
  • Text Data Annotation Tools
  • How does a computer read text data?
  • NLTK
  • spacy
  • PyTorch
  • RegEx
  • Beautiful soap
  • Data Cleaning
  • Regular Expression(Regex)
  • Lemmatization, Stemming and Chunking
  • Tagging (POS and NER Tags)
  • Stopwords and Tokenization
  • Spell Correction
  • Word Segmentation and Processing
  • Bag of Words (BoW)
  • Term Frequency-Inverse Document Frequency (TF-IDF)
  • Word Embeddings
  • Glove, ELMO
  • Word2Vec
  • Hidden Markov Models
  • RNN, LSTM and GRU
  • Seq2Seq modeling
  • Attention mechanism
  • Pointer Generator Network
  • Transformer
  • Transformer-XL
  • Generative Pre-Training Model (GPT)
  • Generative Pre-Training Model -2 (GPT2)
  • Bidirectional Encoder Representations from Transformers (BERT)
  • Text Emotion analysis
  • Recommendation systems
  • Topic Modeling
  • Part Of Speech Tagging (PoS)
  • Named Entity Recognition (NER)
  • Text Summarization
  • Machine Translation (MT)
  • Chatbots
  • Semantic Textual Similarity
  • Text to speech

Key Features

End to end case studies
Build your portfolio
Mock interview
Q & A Session
Assignments
Certification and Job assistance

Related Courses