AutomationEdge Machine Learning Intern Interview Questions and Answers

Use parallel processing, cache optimization, and matrix partitioning for efficient matrix multiplication of huge matrices.

• Utilize parallel processing techniques such as multi-threading or GPU acceleration to distribute the workload and speed up computation.

• Implement cache optimization strategies to minimize cache misses and improve memory access efficiency.

• Divide the matrices into smaller submatrices and perform matrix...read more

Further optimize by fine-tuning hyperparameters, improving data preprocessing, implementing more advanced algorithms, and parallelizing computations.

• Fine-tune hyperparameters using techniques like grid search or random search.

• Improve data preprocessing by handling missing values, scaling features, and encoding categorical variables.

• Implement more advanced algorithms such as ensemble methods like Random Forest or Gradie...read more

Distributed computing involves breaking down tasks into smaller parts and distributing them across multiple computers for faster processing.

• Distributed systems allow for parallel processing of tasks, improving efficiency and scalability.

• Topics include distributed file systems (e.g. HDFS), distributed databases (e.g. Cassandra), and distributed computing frameworks (e.g. Apache Spark).

• Consistency, fault tolerance, and c...read more