Decision Science Analyst

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Decision Science Analyst Interview Questions and Answers

Updated 27 May 2024

Q1. rag pipeline in detail how we achieved

Ans.

The RAG pipeline is a systematic approach to categorize and prioritize risks based on their impact and likelihood.

  • RAG stands for Red, Amber, Green which represent high, medium, and low risk levels respectively.

  • The pipeline involves assessing risks, assigning them a RAG status, and then taking appropriate actions based on the categorization.

  • It helps in identifying critical risks that need immediate attention and resources.

  • The RAG pipeline can be implemented using risk assessme...read more

Q2. any llm deployed in production level

Ans.

Yes, one example of a machine learning model deployed in production is a recommendation system used by e-commerce websites.

  • Recommendation system for e-commerce websites

  • Fraud detection model for financial institutions

  • Customer segmentation model for marketing campaigns

Q3. Transformers architecture in detail

Ans.

Transformers architecture is a type of deep learning model that utilizes self-attention mechanisms.

  • Transformers consist of an encoder and a decoder, each composed of multiple layers of self-attention and feedforward neural networks.

  • Self-attention allows the model to weigh the importance of different input tokens when making predictions.

  • Transformers have been widely used in natural language processing tasks such as machine translation, text generation, and sentiment analysis.

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