Develop a Python class, “CLASSNAME,” equipped with comprehensive logic to tackle all “TOPIC”-related problems efficiently. Streamline your problem-solving with this class.

A lot of us need to use or make spreadsheets for work and other reasons, but not all of us are experts with excel. Don’t remember that formula for excel? Want to figure out something specific? This prompt will give you instructional guide on how to complete your task on excel.

There are so many different terms in the world of blockchain and crypto. A lot of times we have no idea what something means. This will help you figure it out in an easy way and also be able to follow up and expand on other terms you may also want to know.

Provide as much detail as to the project goals as possible in your first message after prompting. When continuing code, prime it with an unambiguous snip of code near where it cut off. Example: Next from “{handleLogin} />” If CodeAssistant tries to leave the rest of the coding to you at any point, regenerate and stop it immediately. Then, put in your message “Continue with implementing..” and state the next part of the application to complete. To avoid issues with conversation token length, get the core of the software completed. Then ask for additional features that are related. Example: “Now add user authentication and login page for admin area.” Once that is coded, go back to this message and edit it so it requests a different bit of the remaining functions. This keeps the core in-memory and generates compatible functions. Use plain and simple language after describing the project. Consider asking GPT to create development plan from your text. Define Milestones for CodeAssistant to follow. Remove the final 2 instructions if you don’t want it’s output to say CodeAssistant.

This dynamic and versatile prompt is designed to turn anyone into a computer troubleshooting expert, regardless of technical skill level. By following a straightforward template, users can diagnose and solve common computer problems with precision. Tailored for a broad audience, from casual users to tech enthusiasts, this guide ensures effective problem-solving through a series of easy-to-follow steps, adaptable to a wide range of computer issues.

Creates a personal developer for any programming use case in any language needed. Will help you identify problems and come up with creative solutions.

The text is asking the reader to act as a machine learning engineer and explain machine learning concepts in simple terms. The first request is asking which machine learning algorithm should be used when there are no labels in the dataset. In machine learning, a dataset is a collection of data used for training a model. Labels refer to the desired output or prediction for each input in the dataset. A machine learning algorithm is a set of instructions that a computer program follows to learn from data and make predictions or decisions. In this case, the algorithm should be able to learn from the data even though there are no labels provided.