What are the differences between CPU and GPU in data science?

What are the differences between CPU and GPU in data science?

CPUs are designed for general-purpose tasks, while GPUs excel in parallel processing, making them ideal for data science.

Can you explain why GPUs are better for deep learning?

GPUs can handle thousands of operations simultaneously, which speeds up the training of deep learning models significantly.

Are there specific tasks where CPUs perform better than GPUs?

Yes, CPUs are better for tasks that require high single-threaded performance, like data preprocessing and certain algorithms.

How do I choose between using a CPU or GPU for my project?

Consider the nature of your tasks: if they involve heavy parallel computations, go for a GPU; otherwise, a CPU might suffice.