In this session, we will explore additional use cases where OpenAI’s GPT-3 and GPT-4 models excel. These models, trained on various language data sets, including code, have proved to be extremely valuable for coding tasks as well. For example, using ChatGPT it’s possible to convert code between programming languages, provide explanations for codes, fix bugs in code, generate SQL queries from natural language descriptions and more. In this session, Kshitij will illustrate how LLM models, such as ChatGPT, can help in coding and application development, accelerating the development process.
In the following video, Kshitij will demonstrate ChatGPT’s prowess in coding tasks by creating a Google Apps Script. The prompt and the output response is available here.
ChatGPT has gained widespread acceptance in the field of ML, playing a crucial role in the development and support of end-to-end ML applications. In the next video, you will learn how ChatGPT can be used for machine learning tasks as well. The prompt and the output responses can be found here.
In the subsequent video, we will see how ChatGPT can be used for building websites using Flask API. The prompt for this task can be found here.
ChatGPT is a powerful tool for software engineers and data scientists alike. With its natural language understanding and code generation capabilities, ChatGPT can assist in various data science tasks. The recent release of ChatGPT’s code interpreter enables one to work with datasets in a sandboxed environment, facilitating the development of data science solutions in a short amount of time.
ChatGPT can automate repetitive tasks such as data inspection, preprocessing and cleaning, code summarisation, documentation and bugs detection. It can generate code snippets and provide guidance on selecting appropriate statistical techniques or machine learning algorithms. Many companies are utilising LLM frameworks to aid with coding tasks. Notable examples in this space include GitHub Copilor, AWS CodeWhisperer, Replit Ghostwriter and more.
In the next segment, we’ll look at a popular prompt engineering technique known as ‘chain-of-thought prompting’.