Natural Language Processing — Prelims Strategy

Prelims Strategy

For Prelims, focus on the fundamental concepts, key techniques, and major applications of Natural Language Processing. Memorize the core components like tokenization, POS tagging, NER, and understand the basic function of word embeddings.

Crucially, differentiate between various AI subfields (NLP vs. Computer Vision vs. Machine Learning). Pay close attention to the evolution of NLP, particularly the shift from rule-based to statistical to deep learning approaches, and the significance of Transformer models (BERT, GPT).

Be aware of prominent Indian government initiatives leveraging NLP, such as the Bhashini platform and its role in Digital India. Questions often test definitional clarity, examples of applications, and the basic understanding of ethical concerns like bias.

Vyyuha recommends creating flashcards for key terms and their definitions, and practicing MCQs that require distinguishing between similar-sounding concepts or identifying the correct application of a technology.

Understanding the 'why' behind each technique (e.g., why embeddings are better than one-hot encoding) will help in eliminating trap options. Current affairs related to AI policy, new LLM releases, and India-specific AI projects are also high-yield areas.