Programmer Think

brief introduction The broadcast describes how NumPy calculates the operation between arrays of different shapes. If it is a larger matrix and a smaller matrix, the smaller matrix will be broadcast to ensure the correct operation. This article will explain in detail the use of broadcast in NumPy with specific examples. Basic broadcasting ...

Visualization and graph analysis of dependency parsing in natural language processing (NLP) Although the effect of dependency parsing is not as good as that of word segmentation and NER, it also has its use value. In our daily work, we have to deal with it. How to analyze the results of dependency parsing, an important aspect is its visualizat ...

1 Principle 1.1 B-tree (1) m-way lookup tree An m-way search tree is either an empty tree or a tree satisfying the following properties: The root has up to m sub trees and has the following structure: ,Is a pointer to a subtree,The key is, In subtreeAll keys in are greater than, less than. In subtreeAll keys in are greater thanIn subtreeAl ...

This is a question that Xiaobai blogger encountered when brushing leetcode. This is the best question in the leetcode question bank recently, so I share this joy here. I hope I can continue to make progress and persevere in the future.   catalogue Topic introduction Problem solving ideas and codes 1. Call function - find/index 2. Viole ...

Reference source: https://github.com/datawhalechina/team-learning-data-mining/tree/master/EnsembleLearning 1. Data set 1.1 background introduction The basic principle of thermal power generation is: when the fuel is burned, it heats water to generate steam, the steam pressure drives the steam turbine to rotate, and then the steam turbine ...

1. GraphSAGE import Thesis title: Inductive Representation Learning on Large Graphs Author: William L. Hamilton, Rex Ying and Jure Leskovec Graph neural network methods proposed before GraphSAGE, such as DeepWalk and GCN, belong to transmissive models. When the structure of the network changes a little, such models need to be retrained, ...

Topic modeling can help developers intuitively understand and explore data, so as to better mine topics in corpus. Successful topic modeling requires multiple iterations: cleaning the data, reading the results, adjusting the preprocessing accordingly, and trying again. This paper analyzes the theme of the New Year greetings of national leaders ...

Blogger in the last article Extracting text relations and creating knowledge map with ltp (based on neo4j) (I) In this paper, the single sentence is analyzed with LTP, the semantic dependency is extracted, and the map is created on neo4j website with python. This chapter is an extension of the previous article. The overall code is similar. This ...

Before forecasting the time series, we need to carry out a series of tests on the data, mainly to test the stability and randomness of the data (white noise test). This paper mainly introduces ADF test and Ljung box test ADF test ADF test, i.e. unit root test, refers to whether there is a unit root in the test series, because the existence ...

MC Dropout refers to Monte Carlo dropout, which can improve the performance of the model in the test stage without changing the network structure and increasing training. The essence is to keep dropout in the active stage during the test. The network is propagated forward for many times. Because the neurons activated by dropout are different ev ...