Nlp

Natural Language Processing enables machines to understand, interpret, and generate human language. This guide covers NLP fundamentals from text preprocessing to deep learning approaches.

Chunk engineering is the art and science of dividing text into optimal segments for NLP processing. This guide covers chunking strategies, evaluation methods, and best practices for RAG pipelines.

Explore how attention mechanisms allow neural networks to focus on relevant information, enabling breakthroughs in NLP and beyond.

BERT is a transformer-based language model that revolutionized NLP by learning bidirectional context. This guide covers its architecture, pre-training objectives, fine-tuning strategies, and variants.

Understand the Transformer architecture that revolutionized NLP and now powers GPT, BERT, and all modern large language models.

Learn how embeddings convert complex data into numerical representations that capture semantic meaning and enable similarity comparisons.

Learn how Word2Vec revolutionized NLP by learning dense word representations that capture semantic relationships.

Learn how GloVe creates word embeddings by leveraging corpus-wide co-occurrence statistics rather than local context windows.

Learn how semantic search uses embeddings and NLP to understand query intent and deliver more relevant results than traditional keyword matching.