Nlp

This document introduces natural language processing, explaining how computers translate between unstructured human language and structured data through techniques like tokenization, stemming, lemmatization, part of speech tagging and named entity recognition.

Comprehensive overview of generative AI tools for code generation, including capabilities, strengths, limitations, and key platforms such as ChatGPT Gemini, Copilot, Polycoder, Watson Code Assistant, Amazon CodeWhisperer, Tab9 and Repl.it. Covers productivity, best practices, and ethical considerations.

Summarizes key concepts in machine learning, deep learning, generative AI cognitive computing, NLP, computer vision, IoT, cloud, and edge computing with real-world applications and model architectures.

This document introduces the fundamentals of Natural Language Processing including text analysis, language understanding, machine translation sentiment analysis, and NLP applications in software development.