IBM Interview Questions, Process, and Tips

Q1. About Machine learning basics, activation functions linear regression, cnn, all basics..
Add your answer
Q2. About project questions, about sdlc basic 3 questions
Add your answer
Q3. About Why not used another model for training?
Add your answer

General aptitude test numerical reasoning, verbaal

Q1. Python question based on list.
Add your answer
Q2. Python question based on data manipulation
Add your answer

Python coding question and couple of SQL questions

Q1. Spark Optimization techniques
Ans. 
Spark optimization techniques focus on improving performance and efficiency of Spark jobs.
• Partitioning data to optimize parallelism

• Caching frequently accessed data

• Using broadcast variables for small lookup tables

• Avoiding shuffling operations whenever possible

• Tuning memory settings for optimal performance
Answered by AI
Add your answer
Q2. Current Project discussions
Add your answer
Q3. Difficulties I have faced during during ETL pipelines
Ans. 
I have faced difficulties in handling large volumes of data, ensuring data quality, and managing dependencies in ETL pipelines.
• Handling large volumes of data can lead to performance issues and scalability challenges.

• Ensuring data quality involves dealing with data inconsistencies, errors, and missing values.

• Managing dependencies between different stages of the ETL process can be complex and prone to failures.
Answered by AI
Add your answer

Q1. Basic walk through of existing role, provided details about the Job description and work schedule.
Add your answer

Q1. Cisco Routing and switching, Wireless, F5 LTM, Firewall, Web-proxy
Add your answer