1.1 Introduction: Overview of Natural Language Processing Key Points Definition of Natural Language: The method of information exchange used by humans for communication, including both spoken and written forms. Ultimate Goal of AI: To enable computers to understand (listen, read) and generate (speak, write) natural language, validated through methods such as the Turing Test. Main … Read more
Introduction Natural Language Processing is a subfield of computer science, information engineering, and artificial intelligence, which involves the interaction between computers and human languages, processing and analyzing large amounts of natural language data through programming. 1Natural Language Processing(NLP) = Computer Science + AI + Computational Linguistics In other words, natural language processing is the ability … Read more
1 Introduction to Algorithms Natural Language Processing (NLP) is an interdisciplinary field that combines computer science, artificial intelligence, and linguistics. It primarily studies how to enable computers to understand, process, generate, and simulate human language, thereby achieving the ability to engage in natural conversations with humans. The underlying principles of natural language processing involve multiple … Read more
1. Overview Natural Language Processing (NLP) is one of the hottest fields in Artificial Intelligence (AI), now primarily referring to large language models. This is thanks to applications that people are enthusiastic about, such as text generators that can write stories, chatbots that can deceive people, and text-to-image programs that produce photo-realistic images. In recent … Read more
Follow the WeChat public account “ML_NLP“ Set as “Starred“, heavy content delivered first-hand! Author: Pratik Bhavsar Translation: ronghuaiyang Introduction Frequently asked questions in NLP interviews. Practicing NLP is one thing, cracking interviews is another. Interviews for NLP positions are very different from general data science roles. In just a few years, these questions have completely … Read more
Follow the WeChat official account “ML_NLP“ Set as “Starred“, heavy content delivered in real-time! Original Link:https://blog.csdn.net/MaggicalQ/article/details/88980534 Introduction This project will use pytorch as the main tool to implement different models (including HMM, CRF, Bi-LSTM, Bi-LSTM+CRF) to solve the problem of Chinese named entity recognition. The article will not involve too much mathematical derivation but will … Read more
Source: PaperWeekly This article is about 2300 words long, and it is recommended to read in 9 minutes. This article mainly discusses solutions to the class imbalance problem, which can be divided into data-level resampling and model loss improvements. The class imbalance issue in NLP tasks is indeed a very common and troublesome problem. Recently, … Read more
It’s another beautiful Wednesday. Hello everyone! Siraj’s machine learning series is back! Do you still remember last week’s discussion about “Voice assistants can analyze the same intent from different language expressions”? NLP In essence, whether it’s a voice assistant or speech recognition, it first converts speech into text, a process known as speech recognition. After … Read more
“The “Levels of Understanding” is a tool for cognitive understanding organized by Robert Dilts, a leading figure in the third generation of NLP. It helps us clearly understand the external and internal worlds. The “Understanding Levels Integration Method” developed based on the “Levels of Understanding” can help individuals break through confusion and connect with the … Read more
Follow the official account “ML_NLP“ Set as “Starred“, receive heavy content promptly! Selected by | Ahmed BESBES Author | Ahmed Besbes Transferred from | Machine Heart This article introduces 7 models for text classification tasks, including traditional bag-of-words models, recurrent neural networks, convolutional neural networks commonly used in computer vision tasks, and RNN + CNN. … Read more