Programming VIP

The network depth of VGG series is improved compared with its previous networks. VGG16 and VGG19 are the representatives of VGG series. This time, VGG16 network is realized based on tensorflow 2.0. 1. Introduction to vgg16 network VGG16 network model stood out in the 2014 ImageNet competition, ranking second in classification tasks and first ...

1. Introduction of GloVe word vector GloVe: The full name is Global Vectors for Word Representations. Its document [2] was presented at the EMNLP conference in 2014. It combines the idea of word vector and matrix decomposition to pre-train the original corpus and get a low-dimensional, continuous and sparse representation. Visualizing the pre- ...

1, Overview of k-nearest neighbor algorithm In short, the k-nearest neighbor algorithm uses the method of measuring the distance between different eigenvalues for classification. k-nearest neighbor Advantages: high precision, insensitive to outliers and no data input assumption. Disadvantages: high computational complexity and space ...

1. Introduction to algorithm         The working principle of k-nearest neighbor algorithm is that there is a sample data set, also known as training sample set, and each data in the sample set has a label, that is, we know the corresponding relationship between each data in the sample set and its classificat ...

Overview of k-nearest neighbor algorithm In short, the k-nearest neighbor algorithm uses the method of measuring the distance between different eigenvalues for classification Working principle of k-nearest neighbor algorithm: there is a sample data set, also known as training sample set, and each data in the sample set has a label, that is, w ...

Starting from 0, data analysis and machine learning in Xueda University are simple and simple to write down the contest experience. This paper uses a variety of machine learning regression algorithms, and also uses deep learning pytorch to build a neural network for regression calculation. 1. Background introduction This is an industrial stea ...

1 Preface Perceptron is a linear classification model of binary classification. Input: the feature vector of the instance; Output: the category of the instance [generally take the binary values of - 1 and + 1]. The perceptron corresponds to the separation hyperplane that divides the instance into positive and negative categories in the input ...

As mentioned earlier, we usually need to clean up the data before we can use large data sets to train learning algorithms. In other words, we need a method to detect and correct errors in the data. Although any given data set may have various bad data, such as outliers or incorrect values, the bad data type we almost always encounter is the lac ...

1 background 1.1 overview of k-nearest neighbor algorithm (1) Introduction of k-nearest neighbor algorithm k-nearest neighbor algorithm is a very effective and easy to master machine learning algorithm. In short, it is an algorithm to classify data by measuring the distance between different eigenvalues. (2) Working principle of k-nearest n ...

Catalog Preface Create a matrix (using ndarray objects) Get the number of rows and columns of a matrix (in two dimensions) Interception of Matrix Intercept by row and column Conditional interception Combination of matrices Create Matrix by Function arange  linspace logspace ones,zeros,eye,empty fromstring fromfunction Operations ...