Sure, here are some examples of how someone could effectively request an engineer to build a text-based neural network:

Clearly define the problem you want to solve: Provide a clear problem statement, explain why it is important and what you expect to achieve from the solution.
Example: "We have a large volume of customer feedback data in free text format, and we want to extract insights from it to improve our product. We need a text-based neural network that can classify the feedback into different categories such as positive, negative or neutral. The expected outcome is to get actionable insights to improve our product."

Provide clear data requirements: Explain what type of data you have and what data format you need for the neural network.
Example: "We have a large dataset of customer feedback in an unstructured text format. We need you to preprocess the data, tokenize the text, and convert it into a suitable format for training the neural network. We can provide you with labeled data for supervised learning."

Specify technical requirements: Explain the technical specifications of the neural network you require.
Example: "We need a text-based neural network that can classify the customer feedback into positive, negative or neutral categories with high accuracy. We prefer a deep learning model that can handle complex features in the text. We prefer to use Python programming language and popular deep learning libraries such as Tensorflow or PyTorch."

Set realistic expectations and timeline: Be clear about your expectations for the project and set a realistic timeline.
Example: "We understand that building a high-quality neural network takes time and effort. We expect the project to take approximately 2-3 months. We would like to receive regular updates on the progress of the project. We are open to discussing the scope of the project and adjusting the timeline based on your recommendations."

By following these guidelines, you can effectively communicate your requirements to the engineer and increase the chances of successful completion of the project.
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