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Scikit learn and Feature Engineering "Data determines the upper limit of machine learning, and the algorithm only approximates this upper limit as much as possible". This sentence well expounds the importance of data in machine learning. Most of the data taken directly are not obvious, unprocessed, or there are a lot of useless d ...

catalogue 1: Introduction to naive Bayes 1.1 classification method based on Bayesian decision theory   1.2 conditional probability 2: Document classification 2.1 constructing word vector from text   2.2 calculating probability from word vector 2.3 modify the classifier according to the actual situation   2.4 document ...

Task05 This study refers to Datawhale open source learning: https://github.com/datawhalechina/fantastic-matplotlib The content is generally derived from the original text and adjusted in combination with their own learning ideas. Personal summary: 1. There are four common style methods: predefined style, custom style, rcparams and matplot librc ...

Support vector machine Support vector machine (SVM) is a very powerful and flexible supervised learning algorithm, which can be used for both classification and regression. In this section, we will introduce the principle of support vector machine and use it to solve the classification problem. First, import the required Library: %matplotlib i ...

Game address portal: CCF big data and computing intelligence competition First read the data import matplotlib.pyplot as plt import seaborn as sns import gc import re import pandas as pd import lightgbm as lgb import numpy as np from sklearn.metrics import roc_auc_score, precision_recall_curve, roc_curve, average_precision_score from sklearn ...

[source code analysis] PyTorch distributed (13) -- back propagation of distributed dataparallel 0x00 summary We have analyzed the forward propagation of Reduer above. This paper then looks at how to carry out back propagation. Other articles in this series are as follows: Automatic differentiation of deep learning tools (1) Automatic different ...

catalogue 2.1 decision tree 2.1.1 sample data set 2.1.2 decision tree visualization 2.2 model classification performance prediction 2.2.1 model stability 2.2.2 SE, SP and ACC classification performance prediction #Code implementation 2.1 decision tree 2.1.1 sample data set The total sample data used in this decision tree constructi ...

introduce MobileViT: a lightweight general vision Transformer for mobile devices. According to the author, this is the first lightweight ViT work that can match the performance of lightweight CNN network, representing SOTA! The performance is better than MobileNetV3, CrossViT and other networks.Lightweight convolutional neural network (CNN) is ...

Introduction to pytorch The article is only used to record your own learning. If there is infringement, delete it immediately Some good websites https://github.com/jcjohnson/pytorch-examples Some small projects of pytorch https://pytorch.org/tutorials/ pytorch official tutorial Fastai Michael Nielsen's "Neural Network and Deep Learn ...

catalogue 1) Write a simple hello world program of command line / console in C#, Java or python to realize the following functions: continuously output 50 lines of "hello cqjtu! Re handover IOT level 2019" on the screen; At the same time, open a network UDP socket and send these 50 lines of messages to another roommate's computer ...