Without high-quality data, there are no high-quality data mining results. Missing data values are one of the common issues encountered in data analysis. When the proportion of missing data is very small, missing records can be directly discarded or handled manually. However, in actual data, missing data often accounts for a significant proportion. In this … Read more
Click the "Xiaobai Learns Vision" above, choose to add "Starred" or "Top" Heavyweight content delivered first hand This article analyzes the reasons for model training not converging or failing from both data and model perspectives. It summarizes four possible reasons from the data side and nine potential issues from the model side. In addition, the … Read more
1. Introduction With the rapid advancement of science and technology, the internet, 5G, big data, and cloud computing are gradually becoming widespread. Various industries in China are undergoing technological innovations, and the pharmaceutical industry is no exception. In response to the increasing number of clinical research studies and to accelerate the market launch of drugs … Read more
1 Overview In recent years, with the increasing prominence of energy shortages and environmental issues, various forms of clean energy such as solar and wind energy have been widely applied. Microgrids, as an effective means of integrating distributed power sources into the grid, have developed rapidly. The integration of a large amount of new energy … Read more
Author: Wei Wei Source:Python Enthusiasts Community This article contains a total of 7800 words, and it is recommended to read for 10+ minutes. This article combines code examples to help you get started with Python data mining and machine learning techniques. This article includes five knowledge points: 1. Introduction to data mining and machine learning … Read more
Case Background Sentiment analysis is an application area of natural language processing (NLP) that aims to understand and analyze the emotions expressed by people in text. This is very useful in areas such as product reviews, social media monitoring, and brand reputation management. Algorithm Principle: Naive Bayes Classifier The Naive Bayes classifier is a simple … Read more
Click the top“Beginner Learning Vision” to select “Star” or “Top” Heavyweight content delivered at the first time Today our goal is to build a classifier that classifies images as “cactus” or “non-cactus”. 01. Dataset This classification problem is one of the Kaggle challenges. The goal is to build a classifier that classifies images as “cactus” … Read more
Source: DeepHub IMBA This article is about 3400 words long and is recommended to read for more than 10 minutes. This article will guide you to recognize human activities using raw data generated by mobile sensors. Human Activity Recognition (HAR) is a method that uses Artificial Intelligence (AI) to recognize human activities from raw data … Read more
Source：Deephub Imba This article is approximately 4000 words, and it is recommended to read in 10minutes In this tutorial, we will use PyTorch-LSTM for deep learning time series prediction. A time series refers to any quantifiable measurement or event that occurs over a period of time. Although this may sound trivial, almost anything can be … Read more
Click on "Little White Learns Vision" above, select "Star" or "Top" Heavyweight content, delivered at the first time In image recognition, the quality of the image directly affects the design and accuracy of the recognition algorithm. Besides optimization on the algorithm side, preprocessing techniques play a crucial role in the entire project, yet people often … Read more