Computer architecture for deep learning

What is the architecture of deep learning?
Deep learning is the branch of machine learning which is based on artificial neural network architecture.
An artificial neural network or ANN uses layers of interconnected nodes called neurons that work together to process and learn from the input data..
What type of computer system is needed for deep learning?
Therefore, you should definitely go for an NVIDIA GPU (not for an AMD GPU), if you want to run deep learning code on GPU.
This is because almost all the GPU-supported Python libraries like CatBoost, TensorFlow, Keras, PyTorch, OpenCV, CuPy have been designed to run on NVIDIA CUDA-enabled GPUs.
Deep learning is the branch of machine learning which is based on artificial neural network architecture.
An artificial neural network or ANN uses layers of interconnected nodes called neurons that work together to process and learn from the input data.
It is used to help teach computers to “see” and to use visual information to perform visual tasks that humans can.
Computer vision models are designed to translate visual data based on features and contextual information identified during training.
Therefore, you should definitely go for an NVIDIA GPU (not for an AMD GPU), if you want to run deep learning code on GPU.
This is because almost all the GPU-supported Python libraries like CatBoost, TensorFlow, Keras, PyTorch, OpenCV, CuPy have been designed to run on NVIDIA CUDA-enabled GPUs

Traditional computer architectures are evolved for procedural and object-oriented programming structure, emphasizing control flow, loop structures,

What is the architecture of deep learning?