|
所在平台: Udemy |
课程主页: https://www.udemy.com/course/natural-language-processing-python-nltk/
课程评论：没有评论
课程名称：NLTK：使用Python构建文档分类器和拼写检查器 课程概述：本课程是关于自然语言处理（NLP）的教程，涵盖了使用著名的Python库Natural Language Toolkit（NLTK）进行NLP的核心基础知识。课程旨在帮助学员熟悉常见概念，如标记、分词、词干提取、词形还原，以及使用正则表达式进行分词或词干提取。它讨论了文本的分类、标记和标准化，此外，还涵盖了一些机器学习算法如朴素贝叶斯。 课程结束后，学员将熟悉自然语言处理（NLP）的基本术语和概念，并能够利用在课程中获得的知识开发NLP应用程序。 自然语言处理（NLP）简介：自然语言处理是计算机程序理解、操作、分析并从人类语言中推导意义的能力。通过利用NLP，开发者可以组织和结构化知识，执行自动摘要、翻译、命名实体识别、关系提取、情感分析、语音识别、主题分割和垃圾邮件检测等任务。 NLTK简介：自然语言工具包（NLTK）是一个用于文本分析的程序模块和数据集的套件，涵盖了符号和统计的自然语言处理。NLTK用Python编写，在教学和研究中已变得非常流行。NLTK包括分词、解析和识别命名实体等功能，具有多种强大的文本处理功能。 关于本课程：本教程的设计旨在让您理解Python中的自然语言处理（NLP）的基本概念，同时我们也将学习一些机器学习算法，因为自然语言处理和机器学习是紧密关联的，NLP利用机器学习技术来理解句子的含义，或如何对用户的输入作出适当的响应。因此，课程结束时，您将对NLP的核心基本概念有清晰的认识，并了解到如何基于这些核心概念开发应用程序。 期待在课程中见到您！
This Natural Language Processing (NLP) tutorial covers core basics of NLP using the well-known Python package Natural Language Toolkit (NLTK). The course helps trainees become familiar with common concepts like tokens, tokenization, stemming, lemmatization, and using regex for tokenization or for stemming. It discusses classification, tagging, normalization of our input or raw text. It also covers some machine learning algorithms such as Naive Bayes.After taking this course, you will be familiar with the basic terminologies and concepts of Natural Language Processing (NLP) and you should be able to develop NLP applications using the knowledge you gained in this course.What is Natural Language Processing (NLP)?Natural language processing, or NLP for short, is the ability of a computer program to understand, manipulate, analyze, and derive meaning from human language in a smart and useful way. By utilizing NLP, developers can organize and structure knowledge to perform tasks such as automatic summarization, translation, named entity recognition, relationship extraction, sentiment analysis, speech recognition, topic segmentation, and spam detection.What is NLTK?The Natural Language Toolkit (NLTK) is a suite of program modules and data-sets for text analysis, covering symbolic and statistical Natural Language Processing (NLP). NLTK is written in Python. Over the past few years, NLTK has become popular in teaching and research.NLTK includes capabilities for tokenizing, parsing, and identifying named entities as well as many more features.This Natural Language Processing (NLP) tutorial mainly cover NLTK modules.About the courseThis Natural Language Processing (NLP) tutorial is basically designed to make you understand the fundamental concepts of Natural Language Processing (NLP) with Python, and we will be learning some machine learning algorithms as well because natural language processing and machine learning move hand in hand as NLP employs machine learning techniques to learn and understand what a sentence is saying, or what a user has said and it sends an appropriate response back. So, by the end of this course, I hope you will have a clear idea, a clear view of the core fundamental concepts of NLP and how we can actually make applications using these core concepts.Looking forward to seeing you in the course.--Keywords: Natural Language Processing (NLP) tutorial; Python NLTK; Machine Learning; Sentiment Analysis; Data Mining; Text Analysis; Text Processing
