Natural Language Processing (NLP) – Complete Course Handwritten Notes

What you will learn

• ✓Understand NLP fundamentals, language structure and NLP architecture.
• ✓Learn text preprocessing, cleaning and normalization techniques.
• ✓Understand tokenization, subword tokenization and linguistic processing.
• ✓Differentiate stemming, lemmatization and morphological analysis.
• ✓Learn text representation using Bag of Words, N-grams and TF-IDF.
• ✓Understand statistical language models, N-grams and perplexity.
• ✓Explore classical NLP algorithms including Naive Bayes, Logistic Regression and SVM.
• ✓Understand word embeddings, Word2Vec, GloVe and FastText.
• ✓Learn RNN, LSTM and GRU architectures for sequential text processing.
• ✓Understand attention mechanisms, Transformers and positional encoding.
• ✓Explore BERT, GPT, T5 and transfer learning techniques.
• ✓Learn Named Entity Recognition, POS tagging and information extraction.
• ✓Understand sentiment analysis, text classification, translation and summarization.
• ✓Evaluate NLP models using precision, recall, F1-score, BLEU and ROUGE.
• ✓Learn NLP error analysis, model optimization and production deployment.
• ✓Understand NLP pipelines, embeddings, RAG and LLM integration.
• ✓Revise important NLP concepts, algorithms and interview questions.