Democratizing machine learning engineering
Best practices, design patterns, and scalable solutions at your finger tips
Best practices, design patterns, and scalable solutions at your finger tips
This application is powered by a large language model (LLM) and may occasionally produce incorrect or misleading information. Use of this application and the information provided is at your own risk. We are not responsible for any errors, omissions, or damages resulting from the use of this app. Please verify any critical details independently.
Our platform leverages Retrieval-Augmented Generation (RAG) to enhance the accuracy and relevance of responses by combining the power of large language models with direct access to trusted machine learning engineering texts. By retrieving specific, authoritative information from your favorite references, we ensure that the answers provided are not only contextual but grounded in reliable sources. This hybrid approach helps reduce the risk of hallucination and offers deeper insights into complex machine learning engineering concepts.
That's ok. Try these prompts to get a sense of what MLE GPT knows:
"Design an ad click prediction system for a social media platform"
"How often should models be retrained?"
"Compare batch prediction with online prediction"
"Provide a list of common feature engineering operations"
"How can I test in production"
"What are some data representation design patterns?"
Please note that the Large Language Model which powers MLE GPT may hallucinate.
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