Discover the intricate world of Natural Language Processing (NLP) in this comprehensive ebook, "NLP, Gen AI, and PE." Begin your journey with a solid foundation in linguistics, exploring essential text processing techniques and statistical language models. Dive into the realms of machine learning and deep learning for NLP, unraveling the complexities of Named Entity Recognition (NER), sentiment analysis, and machine translation.
Navigate through cutting-edge topics like Conversational Agents, Ethical Considerations in NLP, and Recent Advancements in NLP. Explore the impact of NLP in Large Language Models (LLM) and delve into the nuances of word embeddings, attention mechanisms, and the revolutionary Transformer Architecture. This ebook also illuminates the intersection of NLP with other modalities in Multimodal NLP and introduces the concept of Explainable AI in NLP.
Embark on hands-on projects to solidify your understanding and leverage a rich repository of NLP resources and tools. Prepare for interviews with dedicated sections on interview preparation. Witness the future unfold with insights into upcoming trends in NLP.
But the journey doesn't end there - transition seamlessly into the world of Generative AI. Trace the history, types, and training intricacies of Generative Models. Grasp the detailed mathematics behind Generative AI and explore its diverse applications in various industries, art, and creativity. Delve into the collaborative space of Generative AI and human collaboration, while addressing challenges and ethical considerations. Peek into the future, predicting trends that will shape the landscape of Generative AI.
Transitioning further, the ebook explores the fascinating domain of Prompt Engineering. Uncover the psychology of prompts and learn to build effective prompts tailored to different models. Evaluate prompt performance using advanced techniques, with a focus on the mathematics underpinning efficient prompt engineering. Gain insights into popular ChatGPT prompts and the future of prompt design. Address ethical considerations in prompt engineering and collaborative design.