Summary
The web content provides an overview of ChatGPT, its background, and its connection to GPT, Transformers, and Machine/Deep Learning, including a video lecture and open-sourced course materials for related Data Science topics.
Abstract
The article "Zero to ChatGPT" serves as a guide to understanding ChatGPT by tracing its origins back through the GPT models, Transformer architecture, and the broader fields of Machine Learning (ML) and Deep Learning (DL). It emphasizes the importance of foundational knowledge in these areas to fully grasp the capabilities of ChatGPT. The article includes a YouTube video lecture that delves into these topics, suggesting that viewers watch the first part of the series to begin their understanding. Additionally, it points readers to open-sourced course notes on GitHub, which cover a range of Data Science subjects, including Python, ML, DL, and Natural Language Processing (NLP). These notes are intended to provide a comprehensive learning resource. The article also features a photograph of the speaker, inviting readers to learn more about him.
Opinions
To understand ChatGPT, you need to follow GPT, To understand GPT, you need to follow Transformers To understand Transformers, you need to follow Machine/Deep Learning To follow ML-DL, you need to go through first of the talk below -:)
Contents of the talk have been open-sourced at
More about the speaker in the video, by clicking image below:
Jim the AI WhispererSlow down, genius: A simple hack for smarter AI responses
Sheila TeoA deep dive into the strategies I learned for harnessing the power of Large Language Models (LLMs)
Maximilian VogelUpdated Sep-01, 2024. Added New Introductions, Prompts, Lists and Tools
The PyCoachMaster ChatGPT by learning prompt engineering.
