H13-311_V3.5 Exam Dumps - Huawei HCIA-AI Questions and Answers

The order of a tensor refers to its rank, which is the number of dimensions it has. For the tensor [[0,1],[2,3]], the rank is 2 because it is a 2x2 matrix, meaning it has 2 dimensions.

In unsupervised learning, the goal is to find hidden patterns or intrinsic structures in input data without labeled outcomes. One common unsupervised learning task is clustering, where an algorithm groups the dataset into several categories or clusters. Samples within the same cluster have high similarity based on certain features, while samples in different clusters have low similarity. Examples of clustering algorithms include k-means and hierarchical clustering.

AI chips, also known as AI accelerators, are specialized hardware designed to enhance the performance of AI workloads, particularly for tasks like matrix multiplication, which is heavily used in machine learning and deep learning algorithms. These chips optimize operations like matrix multiplications because they are computationally intensive and central to neural network computations (e.g., in forward and backward passes).

HCIA AI References:

Cutting-edge AI Applications: Discussion of AI chips and accelerators, with a focus on their role in improving computation efficiency.

Deep Learning Overview: Explains how neural network operations like matrix multiplication are optimized in AI hardware.

The k-nearest neighbors (k-NN) algorithm is a non-parametric algorithm used for both classification and regression. In classification tasks, it typically uses majority voting to assign a label to a new instance based on the most common class among its nearest neighbors. The algorithm works by calculating the distance (often using Euclidean distance) between the query point and the points in the dataset, and then assigning the query point to the class that is most frequent among its k nearest neighbors.

For regression tasks, k-NN can predict the outcome based on the mean of the values of the k nearest neighbors, although this is less common than its classification use.