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
Click on the “AI有道” above to select the “Star” public account Heavyweight content delivered first-hand This article is adapted from DataWhale Training techniques are very important for deep learning. As a highly experimental science, the same network structure trained with different methods can yield significantly different results. Here, I summarize my experiences over the past … Read more
This article will cover three aspects of one-hot encoding: the principle of one-hot encoding, its classification, and its applications. One-Hot Encoding . One-Hot Encoding 1. The Principle of One-Hot Encoding Feature Digitization: Converts categorical variables (also known as discrete features, unordered features) into a format suitable for machine learning algorithms. Feature Digitization Creates a new … Read more
Honestly, every time I write machine learning code with Scikit-learn, I feel an inexplicable thrill. This library is like our helpful assistant, wrapping complex machine learning algorithms in a simple and easy-to-use way, allowing us to focus on solving real problems rather than getting bogged down in the details of algorithm implementation. Installation and Import … Read more
Scikit-learn: A Powerful Assistant for Building Machine Learning Models To be honest, I have always found machine learning quite mysterious, it sounds very sophisticated. However, since I encountered the Scikit-learn library in Python, I realized that machine learning is not that scary! Today, let’s talk about this super handy tool and see how it helps … Read more