What are the main challenges in scaling deep learning models?

What are the main challenges in scaling deep learning models?

Scaling deep learning models involves several challenges, including data management, computational resources, and model complexity.

Can you elaborate on data management issues?

Certainly! Data management challenges include handling large datasets, ensuring data quality, and efficient data preprocessing.

What about computational resources?

Computational resources can be a bottleneck due to the need for powerful GPUs, memory limitations, and distributed computing complexities.

How does model complexity affect scaling?

Model complexity can lead to longer training times and increased risk of overfitting, making it harder to scale effectively.