Key applications: Sentiment analysis, machine translation, chatbots, NLP in voice assistants (Siri, Alexa), Emerging trends in LLM-powered NLP

Bag of Words (BoW) limitations, TF-IDF mathematics and implementation, Context window concepts

NLTK for education/research, SpaCy for production pipelines, TextBlob for quick prototyping

Word vs. subword tokenization, SpaCy's rule-based tokenizer, Handling multilingual text

Porter vs. Snowball stemmers, SpaCy's lemmatization (with POS tags), When to use each approach

Regex patterns for noise removal, Unicode normalization, Handling emojis/special characters

MultinomialNB for text, Sentiment analysis on product reviews, Bayesian probability refresher

TF-IDF vectorization + LR pipeline, Hyperparameter tuning (C parameter), Feature importance analysis

End-to-end sklearn pipeline, Custom transformers for text, Model persistence with pickle

Word2Vec (CBOW vs Skip-gram), GloVe pretrained vectors, Visualizing embeddings with t-SNE

SpaCy's entity ruler, Custom entity training, BERT-based NER comparison

MFCC extraction steps, Spectrogram interpretation, Audio data augmentation

Whisper architecture overview, DeepSpeech CTC loss, Real-time transcription

Language modeling for ASR, Error correction techniques, Multimodal voice assistants