AI Model Engineer ChatGPT Cheat Sheet

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Automating Code Review

ChatGPT can aid in code review by checking syntax, commenting on code efficiency and suggesting improvements.

Examples:

Check this code snippet: '

{{code_snippet}}

'. Are there any syntax errors or improvements that can be made?
Can this piece of code be optimized: '

{{code_piece}}

'?
What are some good practices for writing code like '

{{code_example}}

'?

Helping in Debugging

ChatGPT can serve as an AI partner in debugging code snippets.

Examples:

Why is this piece of code '

{{code_piece}}

' returning an error?
How can I fix the issue in this ML code: '

{{code}}

'?
What potential problems could arise from this code segment: '

{{code_segment}}

'?

Ideation on Model Architecture

ChatGPT can help propose novel solutions to AI model architecture problems, or explain various approaches to designing AI systems.

Examples:

What is an effective architecture for a

{{application}}

?
Could you explain the advantages and disadvantages of using

{{specified_architecture}}

for my project on

{{task_or_dataset}}

?
What improvements would you suggest for this architecture: '

{{current_architecture}}

'?

AI Ethics Consultation

ChatGPT can provide information on ethical standards and best practices in AI applications and data management.

Examples:

What are some ethical considerations when using

{{AI_model}}

?
Explain the ethical implications of using large-scale AI models.
Can you outline the legal and ethical ramifications of AI-powered surveillance?

Explaining Model Concepts

ChatGPT can be utilized to clarify complex machine learning concepts.

Examples:

What is the concept behind

{{ML_concept}}

?
How does a

{{specific_algorithm}}

work?
Explain the difference between

{{concept1}}

and

{{concept2}}

in machine learning.

Training Collaborative AI

ChatGPT can guide users through the process of training collaborative AI, from selecting data to fine-tuning models.

Examples:

How do I fine-tune

{{AI_model}}

for specific tasks?
What are good practices in collecting data to train a model for the

{{specific_task}}

?
What are the important steps in training a collaborative AI model?
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