In this book I introduce you to ChatGPT, ChatGPT and its capabilities, language models, use cases for ChatGPT. I also explore the technical aspects of chatGPT including transformer architecture, training process for ChatGPT and the dataset used to train ChatGPT. The book further examines Fine-tuning ChatGPT; Applications of ChatGPT and ethical considerations. Buy Now
Chapter One, focuses on introduction and starts by presenting the historical evolution of ChatGPT from GPT one to now ChatGPT 3 as a variant of the GPT (Generative Pre-trained Transformer) language model developed by OpenAI. I then look at how ChatGPT works as a language Model. The chapter then examines what language models are and how ChatGPT compares to other language models and the chapter concludes with examining use cases for ChatGPT. Buy Now
Chapter two focuses on the technical background of ChatGPT. It starts by presenting the transformer architecture of ChatGPT, the training process and the datasets used to train ChatGPT.
Chapter three focuses on the process of fine-tuning ChatGPT and how this improve performance. The chapter explains what fine-tuning is. Its advantages and benefits to improving ChatGPT. I also discuss the types of data and tasks ChatGPT can be fine-tuned for.
Chapter four focuses on the applications of ChatGPT. It starts by presenting an overview of the various natural language processing tasks ChatGPT can be used for. It then presents a discussion of specific use cases for ChatGPT, such as chatbot development, dialogue systems and personalized communication.
Chapter five focuses on ethical considerations. It also discusses the potential biases present in the training data. The chapter further examines the potential impact of ChatGPT on society. The chapter closes with suggestions for responsible use of ChatGPT.
Chapter six presents a conclusion bringing all the key summaries about ChatGPT together. It presents a summary of the capabilities and use cases of ChatGPT. It also discusses future developments and potential advancements in language models.