27 Practical Cases of Python Data Science Libraries (With Code)

27 Practical Cases of Python Data Science Libraries (With Code)

Approximately 8000 words, recommended reading time 15 minutes. This article provides a brief and comprehensive introduction to the currently more common artificial intelligence libraries. In order for everyone to have a preliminary understanding of commonly used Python libraries for artificial intelligence, to choose the libraries that can meet their needs for learning, a brief and … Read more

Introduction to NLP: Rule-Based Chinese Composite Event Extraction with Python Source Code

Introduction to NLP: Rule-Based Chinese Composite Event Extraction with Python Source Code

Author/IT Duck Image/IT Duck, Internet Introduction What is a composite event? Composite events include conditional events, causal events, sequential events, and inverted events. Many real NLP projects require the extraction of composite events, such as event extraction in knowledge graphs to form event-relationship graphs; event extraction in intelligent chat dialogues to identify user intentions. As … Read more

Understanding LDA Algorithm for Keyword Extraction in NLP

Understanding LDA Algorithm for Keyword Extraction in NLP

Click the “MLNLP” above, and choose to add “star” or “top” Heavyweight content delivered promptly Reprinted from the public account: Deep Learning Natural Language Processing Citation How do people conveniently browse and obtain information from a large amount of text? The answer is certainly through keywords. Think about it carefully, how do we extract keywords? … Read more

Beginner’s Guide to Machine/Deep Learning

Beginner's Guide to Machine/Deep Learning

Click the above “Beginner’s Visual Learning” to choose to add “Starred” or “Pinned“. Heavyweight content delivered to you first Author: Song Gu Source: Zhihu Link: https://zhuanlan.zhihu.com/p/33194897 Editor: Wang Meng (Deep Learning Go Go Go public account) Copyright belongs to the author, this article is for academic sharing only. If there is any infringement, please contact … Read more

Practical Deep Learning with Climate Data

The topic of deep learning seems to have lost its previous popularity. Thanks to the myriad tutorials available online, anyone can talk about deep learning for five minutes. But has the threshold for deep learning dropped to the level of statistical methods like EOF decomposition? On one hand, deep learning is overly touted as a … Read more

Essentials of Andrew Ng’s DeepLearning.ai Course: Neural Networks Basics

Essentials of Andrew Ng's DeepLearning.ai Course: Neural Networks Basics

The following notes summarize key points from the second week of the first part of Andrew Ng’s “Neural Networks and Deep Learning” course in the DeepLearning.ai project on Coursera. These notes do not cover all the details of the video lectures. For content omitted in these notes, please refer to Coursera or NetEase Cloud Classroom. … Read more

An Ingenious ChatGPT Attack Method!

An Ingenious ChatGPT Attack Method!

Recently, I came across a very clever attack method using ChatGPT, and I would like to share it with everyone as a reminder. Regardless of whether you understand technology, I recommend that you familiarize yourself with this attack method, as it is better to be prepared. As we all know, current large language models tend … Read more

Implementing Neural Networks from Scratch in Python

Implementing Neural Networks from Scratch in Python

Click the "Learn Visuals" above, select to add "Star" or "Top" Heavy content delivered in real-time There is something that might surprise beginners: Neural network models are not complex! The term ‘neural network’ sounds sophisticated, but in reality, neural network algorithms are simpler than people think. This article is entirely prepared for beginners. We will … Read more

Comparison and Introduction of Different Distance Metrics in KNN

Comparison and Introduction of Different Distance Metrics in KNN

Source: DeepHub IMBA This article is about 4200 words long and is recommended to be read in over 10 minutes. This article demonstrates the use of KNN with three different distance metrics. The k-nearest neighbors (KNN) algorithm is a simple yet powerful algorithm that can be used for classification and regression tasks. It is easy … Read more

The Lazy Algorithm – KNN

The Lazy Algorithm - KNN

Total Article 77 This article introduces one of the most basic and also the most “lazy” algorithms in machine learning – KNN (k-nearest neighbor). Do you know why it is called the laziest? 01|Algorithm Introduction: KNN is short for k-nearest neighbor, which indicates the K closest points. This algorithm is commonly used to solve classification … Read more