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所在平台: Udemy |
课程主页: https://www.udemy.com/course/la-hoang-quy-introduction-to-transformer-for-nlp-with-python/
课程评论：没有评论
课程名称：Python自然语言处理中的Transformer入门 课程概述： 对自然语言处理（NLP）感兴趣吗？那么这个课程非常适合你！自从Transformer问世以来，深度学习发生了巨大的变革。机器学习能够生成与人类创作几乎无法区分的文本，许多NLP任务，如机器翻译、问答系统、推理和命名实体识别等，都取得了新的最优表现。在本课程中，您将学习适用Transformers的实用技能，以及其背后详细的理论。 本课程与其他课程的不同之处在于： 1. 涵盖了所有基本的自然语言处理技术，帮助您理解NLP的基本概念。 2. 重点介绍在NLP中非常受欢迎的GPT-2、NER和BERT。 3. 提供大量实践项目，配有详细的逐步解释备忘录，便于随时阅读。 课程分为四个主要部分： 1. 基础自然语言处理 2. 基础Transformer 3. 使用GPT-2进行文本生成 4. 文本分类 **第1部分：使用Transformer** 在这一部分，您将了解自然语言处理的基础知识，包括自然语言处理的定义、词干提取和词形还原、短语分块与词袋模型等。同时，我们将完成三个小项目：性别识别、情感分析、主题建模。 **第2部分：基础Transformer** 在这一部分，您将学习Transformer的原理，并引入Hugging Face和GPT-2的概念，以更好地理解Transformers的强大功能。我们将实现两个项目：IMDB项目与问答项目的实现。 **第3部分：项目：使用GPT-2进行文本生成** 在这个项目中，我们将使用GPT-2生成文本，以巩固所学内容，并展示如何快速生成文本。 **第4部分：Token分类** 在这一部分，我们将学习如何使用Transformer对文本进行分类，还将了解命名实体识别（NER）的相关内容。该部分的主要项目是一个更复杂的问答项目。 通过这个课程，您将掌握NLP的基础知识和Transformer的应用，增强您在自然语言处理领域的技能。
Interested in the field of Natural Language Processing (NLP)? Then this course is for you!Ever since Transformers arrived on the scene, deep learning hasn't been the same.Machine learning is able to generate text essentially indistinguishable from that created by humansWe've reached new state-of-the-art performance in many NLP tasks, such as machine translation, question-answering, entailment, named entity recognition, and moreIn this course, you will learn very practical skills for applying transformers, and if you want, the detailed theory behind how transformers and attention work.There are several reasons why this course is different from any other course. The first reason is that it covers all basic natural language process techniques, so you will have an understanding of what natural language processing is. The second reason is that it covers GPT-2, NER, and BERT which are very popular in natural language processing. The final reason is that you will have lots of practice projects with detailed explanations step-by-step notebook so you can read it when you have free time.The course is split into 4 major parts:Basic natural language processingFundamental TransformersText generation with GPT-2Text classificationPART 1: Using TransformersIn this section, you will learn about the fundamental of the natural language process. It is really important to understand basic natural language processing before learning transformers. In this section we will cover:What is natural language processing (NLP)What is stemming and lemmatizationWhat is chunkingWhat is a bag of words?In this section, we will build 3 small projects. These projects are:Gender identificationSentiment analyzerTopic modellingPART 2: Fundamental transformerIn this section, you will learn how transformers really work. We will also introduce the new concept called Hugging face transformer and GPT-2 to have a big understanding of how powerful the transformer is.In this section, we will implement two projects.IMDB project Q & A project implementationPART 3: Project: Text generation with GPT-2In this project, we will generate text with GPT-2. This is a project for us to practice and reinforce what we have learned so far. It will also demonstrate how text is generated quickly with a transformer.PART 4: Token classification.In this section, we will learn how to classify a text using a transformer. We will also learn about NER which is also popular in transformers. The main project in this section is about Q &A project and it will be more advanced than the previous Q & A project.
