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所在平台: Udemy |
课程主页: https://www.udemy.com/course/natural-language-processing-for-text-analysis-with-spacy/
课程评论：没有评论
课程名称：使用spaCy进行文本分析的自然语言处理 课程概述：自然语言处理（NLP）是人工智能（AI）的一个子领域，旨在使计算机理解人类的口语和书面语言。NLP 有多种应用，包括文本到语音和语音到文本转换、聊天机器人、自动问答系统、自动图像描述生成和视频字幕等。随着 ChatGPT 的推出，NLP 将变得越来越流行，可能会在这一 AI 分支领域带来更多就业机会。SpaCy 框架因其处理大文本数据集的能力、信息抽取、为后续 AI 模型预处理文本以及开发生产级 NLP 应用程序的能力，而成为 Python NLP 生态系统的重要工具。 如果你是 NLP 新手，欢迎报名参加我最新的课程，学习自然语言处理和使用 spaCy 开发 NLP 模型。 课程分为三个主要部分： 第一二部分：课程将介绍构建 NLP 模型所需的主要 Python 概念，包括如何使用 Google Colab（一个在线 Jupyter 实现，免去在计算机上安装包的麻烦）。随后，课程将介绍 NLP 的基本概念和 spaCy 框架，使学员熟悉 NLP 理论和 spaCy 架构。 第三至五部分：这些部分将集中讲解基本的自然语言处理概念，如词性标注、词形还原、词干提取、命名实体识别、停用词、依存解析、词语和句子相似度及分词等及其在 spaCy 中的实现。 第六部分：通过一些实际项目，你将学习如何使用 spaCy 进行真实世界的应用。 额外部分涵盖了一些 Python 数据科学基础知识。 为什么要参加我的课程？我的课程是一门注重实践的培训，涉及真实的 Python 社交媒体挖掘。你将学习如何进行文本分析和自然语言处理（NLP），从非结构化文本数据中获取洞察，包括推文分析。我的课程为进行实际的社交媒体挖掘奠定了基础。通过参加此课程，你将迈出数据科学之路的重要一步，成为利用文本力量提取洞察和识别趋势的专家。 我拥有牛津大学的地理与环境硕士学位和剑桥大学的集中的数据科学博士学位（热带生态与保护）。我在分析来自不同来源（包括文本来源）的实际数据、为国际同行评审期刊发表文章以及进行数据科学咨询工作方面拥有多年经验。此外，我将提供持续的支持，以确保你能从投资中获得最大价值！ 现在报名吧！
Natural Language Processing (NLP) is a subfield of Artificial Intelligence (AI) to enable computers to comprehend spoken and written human language. NLP has several applications, including text-to-voice and speech-to-text conversion, chatbots, automatic question-and-answer systems (Q & A), automatic image description creation, and video subtitles. With the introduction of ChatGPT, NLP will become more and more popular, potentially leading to increased employment opportunities in this branch of AI. The SpaCy framework is the workhorse of the Python NLP ecosystem owing to (a) its ability to process large text datasets, (b) information extraction, (c) pre-processing text for subsequent use in AI models, and (d) Developing production-level NLP applications. IF YOU ARE A NEWCOMER TO NLP, ENROLL IN MY LATEST COURSE ON HOW TO LEARN ALL ABOUT NATURAL LANGUAGE PROCESSING (NLP) AND TO DEVELOP NLP MODELS USING SPACYThe course is divided into three main parts:Section 1-2: The course will introduce you to the primary Python concepts you need to build NLP models, including getting started with Google Colab (an online Jupyter implementation which will save the fuss of installing packages on your computers). Then the course will introduce the basic concepts underpinning NLP and the spaCy framework. By this end, you will gain familiarity with NLP theory and the spaCy architecture.Section 3-5: These sections will focus on the most basic natural language processing concepts, such as: part-of-speech, lemmatization, stemming, named entity recognition, stop words, dependency parsing, word and sentence similarity and tokenization and their spaCy implementations.Section 6: You will work through some practical projects to use spaCy for real-world applicationsAn extra section covers some Python data science basics to help you. Why Should You Take My Course?MY COURSE IS A HANDS-ON TRAINING WITH REAL PYTHON SOCIAL MEDIA MINING- You will learn to carry out text analysis and natural language processing (NLP) to gain insights from unstructured text data, including tweets.My course provides a foundation to conduct PRACTICAL, real-life social media mining. By taking this course, you are taking a significant step forward in your data science journey to become an expert in harnessing the power of text for deriving insights and identifying trends.I have an MPhil (Geography and Environment) from the University of Oxford, UK. I also completed a data science intense PhD at Cambridge University (Tropical Ecology and Conservation). I have several years of experience analyzing real-life data from different sources, including text sources, producing publications for international peer-reviewed journals and undertaking data science consultancy work. In addition to all the above, you'll have MY CONTINUOUS SUPPORT to ensure you get the most value out of your investment!ENROLL NOW:)
