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所在平台: Udemy |
课程主页: https://www.udemy.com/course/natural-language-processing-basics-to-advanced-course/
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课程名称：使用 Python 进行自然语言处理 课程概述： 在本课程中，您将由经验丰富的专业人士学习自然语言处理（NLP）。赋予机器从自然语言中提取未结构化数据意义的能力前景广阔。预计到2025年，全球NLP市场将超过340亿美元，年均增长率将达到21.5%，对NLP技能的需求将十分旺盛。在本课程中，我将对NLP的各个主题进行详尽讲解，以简单易懂的方式阐释NLP概念，同时使用Python及其库如NLTK、spaCy、TensorFlow和PyTorch进行实践实现。我还将讨论多种主题，包括文本预处理、文本分类、文本摘要、主题建模和词嵌入。此外，我将覆盖NLP在医疗、金融等多个领域的应用。本课程将帮助您入门并逐步掌握NLP的相关技能。 在本视频课程中，您将学习以下内容： - 自然语言处理简介 - 自然语言处理在金融和医疗等领域的应用 - 使用NLTK和spaCy进行词干提取和词形还原 - TF-IDF和词袋模型表示 - 使用spaCy进行命名实体识别 - 使用spaCy v3库进行自定义命名实体识别 - Word2Vec模型及其自定义模型实现 - 使用Python进行文本数据集的探索性数据分析 - 文本聚类 - 使用Tensorflow在Python中进行神经网络文本分类 - 使用Tensorflow在Python中进行卷积神经网络（CNN）文本分类 - 使用Tensorflow在Python中进行长短期记忆（LSTM）网络文本分类 - 使用PyTorch库进行文本分类 - 使用BERT Transformers进行文本分类 - 使用spaCy v3库进行文本分类 - 使用HuggingFace进行零样本文本分类 - LDA主题建模 - Top2Vec主题建模 - BERTopic主题建模 - 使用gensim和Python进行抽取式文本摘要 - 使用Google PEGASUS进行概括式文本摘要 - 使用HuggingFace进行抽取式问答 - HayStack问答演示 如需了解更高级的NLP内容，请访问我的YouTube频道。
In this course you will be learning about Natural Language Processing (NLP) from an experienced professional. Giving machines the capacity to find meaning in unstructured data pulled from natural language holds notable promise. By 2025, the global NLP market is expected to reach over $34 billion, growing at a CAGR of 21.5% and there would be high demand for NLP skills. In this course I cover length and breadth of topics in NLP. I explain NLP concepts in a simple way along with practical implementation in Python using libraries like NLTK, spaCy, TensorFlow and PyTorch. I also discuss various topics like text pre-processing, text classification, text summarization, topic modelling and word embeddings. I also cover NLP applications in various domains like healthcare, finance. I am sure this course should help you in getting started and also become proficient in NLPIn this video course you will learn the following about Natural Language Processing:Introduction to NLPIts Applications in domains like finance and healthcareStemming and Lemmatimzation with NLTK and spaCyTF-IDF, Bag of Words RepresentationNamed Entity Recognition with spaCy in pythonCustom Named Entity Recognition using spaCy v3 libraryWord2Vec model and custom word2vec model in pythonExploratory data analysis on text dataset using pythonText ClusteringText Classification with Neural network using Tensorflow in PythonText Classification with Convolutional Neural Network( CNN) using Tensorflow in PythonText Classification with Long Short Term memory( LSTM) networks using Tensorflow in PythonText Classification using PyTorch libraryText Classification using BERT TransformersText Classification using spaCy v3 libraryZero shot text classification using HuggingFaceLDA topic modellingTop2Vec Topic ModellingBERTopic Topic ModellingExtractive Text Summarization using gensim and pythonAbstractive Text Summarization using Google PEGASUSExtractive Question Answering with HuggingFaceAspect Based Sentiment AnalysisHayStack Question Answering DemoFor advanced NLP content check out my Youtube Channel
