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所在平台: Udemy |
课程主页: https://www.udemy.com/course/awesome-natural-language-processing-tools-in-python/
课程评论：没有评论
课程名称：Python中的优秀自然语言处理工具 课程概述： 本课程将探索如何使用Python处理人类语言，帮助学习者理解和运用自然语言处理（NLP）工具。在全球有超过7000种语言的背景下，机器是否能够理解并处理这些语言呢？如果你对自然语言处理项目感兴趣，并且想了解情感分析、文本分类、摘要及其他多个NLP任务的基础知识，那么本课程适合你。 自然语言处理是数据科学的一个令人兴奋的领域，但学习的内容繁多且不断更新。本课程将指导你了解进行NLP项目所需的15种以上的工具，将重点放在工作流程和所需工具上。课程采用简单的NLP项目生命周期的视角，覆盖从文本数据抓取、清洗和预处理到使用各种工具（如NeatText、Ftfy、Regex等）处理非结构化文本的各个方面。 课程内容包括： - 理解分词的重要性及其工作原理 - 在Python中进行风格分析 - 使用Spacy、TextBlob、Flair和NLTK进行NLP - 机器学习与Transformers、TextBlob、Flair等进行文本分类 - 使用Streamlit构建NLP应用 - 从零开始进行情感分析，使用多个NLP包 - 从文本数据构建特征（Word2Vec、FastText、Tfidf等） 该课程不仅关注NLP项目每个步骤中有用的工具，还教授这些工具的工作原理及如何从零开始构建简单的函数。希望你能在课程中与我们一起学习，提升自己的理解能力。建议边写边码，不要仅仅观看视频。同时，若视频速度较快，可以调节至-0.75倍速。课程的预备知识要求为对Python的理解。 请注意，本课程并不是对NLP的理论介绍或高级概念探讨，而是专注于NLP项目工作流中使用的工具。加入我们，一起探索自然语言处理的世界！
Do you know that there are over 7000 human languages in the world? Is it even possible to empower machines and computers to be able to understand and process these human languages? In this course we will be exploring the concept and tools for processing human (natural) language in python. Hence if you are interested in Natural Language Processing Projects and are curious on how sentiment analysis,text classification,summarization,and several NLP task works? Then this course is for you.Natural Language Processing is an exciting field of Data Science but there are a lot of things to learn to keep up. New concepts and tools are emerging every day. So how do you keep up ? In this course on Awesome Natural Language Processing Tools In Python we will take you on a journey on over 15+ tools you need to know and be aware of when doing an NLP project in a format of a workflow.Tools and technologies are always changing but workflows and systems remain for a long time hence we will be focusing on the workflow and the tools required for each. The course approaches Natural Language Processing via the perspective of using a workflow or simple NLP Project Life Cycle. By the end of this exciting course you will be able to Fetch Textual Data From most document(docx,txt,pdf,csv),website etc Clean and Preprocess unstructured text data using several tools such as NeatText,Ftfy,Regex,etc Understand how tokenization works and why tokenization is important in NLP Perform stylometry in python to identify and verify authors NLP with Spacy,TextBlob,Flair and NLTK Learn how to do text classification with Machine Learning,Transformers, TextBlob ,Flair,etc Build some awesome NLP apps using Streamlit Perform Sentiment Analysis From Scratch and with Several NLP Packages Build features from textual data- Word2Vec,FastText,Tfidf And many moreThis comprehensive course focuses on not just the various tools that are useful in each step of an End to End NLP project but also how they work and how to build simple functions from scratch for your task.Join us as we explore the world of Natural Language Processing.See you in the Course,Stay blessed.Tips for getting through the coursePlease write or code along with us do not just watch,this will enhance your understanding.You can regulate the speed and audio of the video as you wish,preferably at -0.75x if the speed is too fast for you.Suggested Prerequisites is understanding of PythonThis course is NOT a 'Theoretical Introduction to NLP' nor 'Advanced Concepts in NLP' although we try our best to cover some concepts for the beginner and the pro. Rather it is about the tools used for NLP Project workflow.
