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10+ GeeksMetrics Interview Questions and Answers

Updated 14 Nov 2024

Q1. How to design large scale machine learning system

Ans.

Designing large scale ML systems requires careful consideration of data, infrastructure, algorithms, and deployment.

  • Identify the problem and define the objectives

  • Collect and preprocess large amounts of data

  • Choose appropriate algorithms and train models

  • Deploy models on scalable infrastructure

  • Monitor and evaluate performance regularly

  • Continuously improve the system based on feedback

  • Consider ethical and legal implications

  • Collaborate with cross-functional teams

  • Examples: Google's ...read more

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Q2. Architecture design for large scale app

Ans.

Architecture design for large scale app involves distributed systems, microservices, and scalability.

  • Use distributed systems to handle large amounts of data and traffic

  • Implement microservices to break down the app into smaller, manageable components

  • Ensure scalability by designing for horizontal scaling and load balancing

  • Use caching and database sharding to improve performance

  • Implement fault tolerance and disaster recovery measures

  • Consider using containerization and orchestrat...read more

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Q3. Multithreading and multiprocessing use cases

Ans.

Multithreading and multiprocessing are used to improve performance by executing multiple tasks simultaneously.

  • Multithreading is useful for I/O-bound tasks, such as web scraping or file processing.

  • Multiprocessing is useful for CPU-bound tasks, such as image processing or scientific computing.

  • Both can be used together to achieve maximum performance.

  • Care must be taken to avoid race conditions and deadlocks.

  • Python's Global Interpreter Lock (GIL) limits the effectiveness of multit...read more

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Q4. Live coding to parse logs from a given file

Ans.

Live coding to parse logs from a given file

  • Choose a programming language

  • Read the file line by line

  • Use regular expressions to extract relevant information

  • Store the extracted data in a structured format

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Q5. System design for big data application

Ans.

System design for big data application involves selecting appropriate technologies, designing data architecture, and ensuring scalability.

  • Choose appropriate technologies for data storage, processing, and analysis

  • Design data architecture that can handle large volumes of data

  • Ensure scalability by using distributed systems and load balancing

  • Consider security and privacy concerns

  • Examples of technologies: Hadoop, Spark, NoSQL databases, distributed file systems

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Q6. Hash Table implementation

Ans.

Hash table is a data structure that maps keys to values using a hash function.

  • Hash function maps keys to indices in an array

  • Collisions can occur when two keys map to the same index

  • Collision resolution techniques include chaining and open addressing

  • Hash tables have O(1) average case time complexity for insert, delete, and search operations

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Q7. Memory management in python

Ans.

Python uses automatic memory management through garbage collection.

  • Python uses reference counting to keep track of objects in memory.

  • When an object's reference count reaches zero, it is deleted by the garbage collector.

  • Python also uses a cyclic garbage collector to handle circular references.

  • Memory can be managed manually using the 'gc' module.

  • Python's memory management is efficient and transparent to the programmer.

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Q8. how does random forest work

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Q9. Merge the two sorted array

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Q10. what is iverfitting

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