Micro1 Interview Questions, Process, and Tips

Q1. How LLM works and what all LLMS have been used
Ans. 
LLM stands for Large Language Models, which are AI models trained on vast amounts of text data to understand and generate human language.
• LLMs use deep learning techniques to process and understand language data.

• Some popular LLMS include GPT-3 (Generative Pre-trained Transformer 3) by OpenAI and BERT (Bidirectional Encoder Representations from Transformers) by Google.

• LLMs have been used in various applications such as n...read more
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Q2. How RAG pipeline works
Ans. 
RAG pipeline is a framework used for ranking and generation tasks in natural language processing.
• RAG stands for Retrieve, Aggregate, Generate.

• It involves retrieving relevant information, aggregating it, and generating a response.

• Used in tasks like question answering and text summarization.

• Can be implemented using transformers like BERT or T5.
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Write a program to make a code editor

Q1. Basics of react
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Q2. Basics of javascript
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Q1. Explain in brief about data pipeline
Ans. 
Data pipeline is a series of tools and processes used to collect, process, and move data from one system to another.
• Data pipeline involves extracting data from various sources

• Transforming the data into a usable format

• Loading the data into a destination for storage or analysis

• Examples include ETL (Extract, Transform, Load) processes, Apache Kafka, and AWS Data Pipeline
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Q2. Explain about cache in fast api
Ans. 
Cache in FastAPI is used to store and retrieve data to improve performance.
• Cache in FastAPI can be implemented using tools like Redis or Memcached.

• It helps in reducing the response time by storing frequently accessed data.

• Cache can be used to store database query results, API responses, or any other computationally expensive data.

• By caching data, FastAPI can serve requests faster and improve overall application perform
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