COMPUTER FUNDAMENTALS

EMERGING TRENDS IN COMPUTING

ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING

Question [CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
Deep learning neural network training requires a lot of matrix calculations. Generally, we need to use hardware to enable the computer to have parallel computing capabilities. The following hardware devices can provide parallel computing capabilities:
A
Motherboard
B
RAM
C
CPU
D
GPU
Explanation: 

Detailed explanation-1: -A CPU with the Advanced Vector Extensions (AVX) instruction set. In general, any CPU after 2011 will contain this instruction set. Intel CPUs are recommended, though not required. They have an optimized Intel Machine Learning library that offers performance gains for certain Machine Learning algorithms.

Detailed explanation-2: -Deep learning models are trained by using large sets of labeled data and neural network architectures that learn features directly from the data without the need for manual feature extraction.

Detailed explanation-3: -The standard method for training neural networks is the method of stochastic gradient descent (SGD). The problem of gradient descent is that in order to determine a new approximation of the weight vector, it is necessary to calculate the gradient from each sample element, which can greatly slow down the algorithm.

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