Colab platform uses gensim package to realize Word2Vec and fasttext (cbow and skip gram)

It is not advisable to build wheels repeatedly. We should reasonably learn to adjust (tou) package (lan)! Gensim is an open source library that can be used for unsupervised learning and natural language processing. The programming languages are Python and python. More details can be queried on the official website. First import the basic pack ...

Posted by paolo on Thu, 31 Mar 2022 00:58:55 +0300

Summary of some topics in the Python linked list of Blue Bridge Cup

Blue Bridge Cup Python topic sorting - linked list The following topics are selected from Blue bridge cloud course: https://www.lanqiao.cn/courses/5456 LeetCode: https://leetcode-cn.com/problemset/all/ LeetCode83: delete duplicate elements in the sorting linked listSword finger offer22: delete duplicate items in the linked listSword fing ...

Posted by simonb on Wed, 30 Mar 2022 14:36:43 +0300

Analysis of 3DMM sample source code of Face3D learning notes [middle and lower] reconstructing a 3D model from the feature points of a 2D picture -- the gold standard algorithm

Write in front In order to ensure that the whole sample project is more intuitive and easy to understand, numpy version will be used to display the source code of some functions, while numpy version library is not used in the sample program. There will be a mark in front of the original code where there is a difference between Python version a ...

Posted by janet287 on Tue, 29 Mar 2022 16:32:45 +0300

Deep learning classic network analysis: DenseNet

1. Background introduction    DenseNet is CVPR's Best Paper in 2017. It breaks away from the stereotype of deepening the number of network layers (ResNet) and widening the network structure (Inception) to improve the network performance. From the perspective of features, through feature reuse and bypass setting, it not only great ...

Posted by MattG on Sun, 27 Mar 2022 04:05:43 +0300

(Tianchi) zero foundation introduction data mining - Summary notes of heartbeat signal classification and prediction

1. Simple linear weighted fusion import numpy as np import pandas as pd from sklearn import metrics ## Generate some simple sample data, test_prei represents the predicted value of the ith model test_pre1 = [1.2, 3.2, 2.1, 6.2] test_pre2 = [0.9, 3.1, 2.0, 5.9] test_pre3 = [1.1, 2.9, 2.2, 6.0] # y_test_true represents the true value of the se ...

Posted by jeicrash on Sat, 26 Mar 2022 11:41:48 +0300