Toggle Side Panel
Close search
Course Content
23AMB302 – NATURAL LANGUAGE PROCESSING
0/42
The NLP Landscape: History and Applications
Text Preprocessing: Tokenization
Stemming – Lemmatization
Stopword Removal
Regular Expressions for Text Pattern Matching
WordNet and Lexical Resources
Basic String Matching and Edit Distance
Language Modeling: N-grams and Smoothing Techniques
Basic Text Classification: Naive Bayes
Logistic Regression
Vector Space Models: Bag-of-Words (BoW)
TF-IDF
Word Embeddings: Word2Vec Skip-gram – CBOW
GloVe
Evaluation Metrics: Precision
Recall – F1-Score
Neural Networks for NLP
Recurrent Neural Networks (RNNs)
LSTMs and GRUs
Sequence-to-Sequence Models (Seq2Seq)
Attention Mechanism
Introduction to the Transformer Architecture
Self-Attention
Encoder-Decoder Structure
Transfer Learning in NLP
Transformer-based Models: BERT
GPT, T5
Fine-Tuning Strategies for Downstream Tasks
Text Classification, NER, Q&A
Prompt Engineering
In-Context Learning
Introduction to Text Generation
Hugging Face Ecosystem: Transformers Library
Datasets and Model Hub
Advanced Tasks: Named Entity Recognition (NER)
Sentiment Analysis
Machine Translation
Text Summarization
Building RAG (Retrieval-Augmented Generation) Applications
Bias and Fairness in NLP Models
Explainability and Interpretability for NLP
Current Trends and Ethics
23AMB302 NLP
Previous
Next
screen tagSupport

Report

Harassment or bullying behavior
Contains mature or sensitive content
Contains misleading or false information
Contains abusive or derogatory content
Contains spam, fake content or potential malware

Block Member?

Please confirm you want to block this member.

You will no longer be able to:

  • See blocked member's posts
  • Mention this member in posts
  • Invite this member to groups
  • Message this member
  • Add this member as a connection

Please note: This action will also remove this member from your connections and send a report to the site admin. Please allow a few minutes for this process to complete.

Report

You have already reported this .