Benchmarking Machine Learning Architectures for High-Dimensional Data Processing

This ArXiv paper provides valuable insights into the performance of machine learning and deep learning models when processing high-dimensional data, a crucial area of research. Benchmarking in local and distributed environments offers a comprehensive evaluation, helping to identify optimal architectures for real-world applications.

• •Comprehensive benchmarking of machine learning and deep learning models.
• •Evaluation in both local and distributed computing environments.
• •Aids in selecting the best architectures for high-dimensional data tasks.