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所在平台: Udemy |
课程主页: https://www.udemy.com/course/natural-language-processing-nlp-using-nltk-in-python/
课程评论：没有评论
课程名称：使用Python中的NLTK进行自然语言处理（NLP） 课程概述： 自然语言处理（NLP）是数据科学中最有趣的一个子领域，能够强有力地解释和处理口语和书面语言。NLP广泛应用于客户支持、产品情感分析以及提供直观的用户界面。如果您希望利用NLP构建高性能的日常应用程序，本课程将是您的理想选择。 本课程将教您使用流行的数据科学概念NLP编写应用程序。您将学习自然语言理解、自然语言处理和句法分析的各种概念。您将掌握文本分类的实现、词性标注、词语标记等技能，并深入分析句子结构，掌握句法和语义分析。通过实际演示、清晰的解释和有趣的现实例子，您将获得多样化的NLP技能，并将其应用到自己的应用程序中。 课程内容和结构： 该培训项目包含两个完整的课程，旨在为您提供全面的培训。第一个课程“自然语言处理实践”通过实际演示和实例帮助您掌握NLP技能，赋予您深度学习和NLP的多样化技能。第二个课程“使用Python中的NLTK开发NLP应用程序”涵盖了多个概念，从初级到高级，让您能够有效使用NLTK进行文本分类、词性标注等任务，并分析句子结构，掌握句法和语义分析。 完成本课程后，您将能够利用深度学习和NLP技术，使用Python和NLTK构建智能系统。 讲师介绍： 课程由业界知名的专家授课： - Smail Oubaalla：软件工程师，善于设计和管理项目，热爱运动和美食。 - Krishna Bhavsar：拥有近10年NLP、社交媒体分析及文本挖掘经验，对多个工业领域有深入了解。 - Naresh Kumar：全栈架构师，具有丰富的互联网应用开发经验，积极参与开源项目。 - Pratap Dangeti：机器学习和深度学习解决方案开发者，人工智能爱好者，曾在多个高端研究项目中担任重要角色。 这个课程为您提供了扎实的NLP基础和实践经验，准备好让您的应用程序更智能、更高效。
Natural Language Processing (NLP) is the most interesting subfield of data science. It offers powerful ways to interpret and act on spoken and written language. It's used to help deal with customer support enquiries, analyse how customers feel about a product, and provide intuitive user interfaces. If you wish to build high performing day-to-day apps by leveraging NLP, then go for this course.This course teaches you to write applications using one of the popular data science concepts, NLP. You will begin with learning various concepts of natural language understanding, Natural Language Processing, and syntactic analysis. You will learn how to implement text classification, identify parts of speech, tag words, and more. You will also learn how to analyze sentence structures and master syntactic and semantic analysis. You will learn all of these through practical demonstrations, clear explanations, and interesting real-world examples. This course will give you a versatile range of NLP skills, which you will put to work in your own applications.Contents and OverviewThis training program includes 2 complete courses, carefully chosen to give you the most comprehensive training possible.The first course, Natural Language Processing in Practice, will help you gain NLP skills by practical demonstrations, clear explanations, and interesting real-world examples. It will give you a versatile range of deep learning and NLP skills that you can put to work in your own applications.The second course, Developing NLP Applications Using NLTK in Python, course is designed with advanced solutions that will take you from newbie to pro in performing natural language processing with NLTK. You will come across various concepts covering natural language understanding, natural language processing, and syntactic analysis. It consists of everything you need to efficiently use NLTK to implement text classification, identify parts of speech, tag words, and more. You will also learn how to analyze sentence structures and master syntactic and semantic analysis.By the end of this course, you will be all ready to bring deep learning and NLP techniques to build intelligent systems using NLTK in Python.Meet Your Expert(s):We have the best work of the following esteemed author(s) to ensure that your learning journey is smooth:Smail Oubaalla is a talented Software Engineer with an interest in building the most effective, beautiful, and correct piece of software possible. He has helped companies build excellent programs. He also manages projects and has experience in designing and managing new ones. When not on the job, he loves hanging out with friends, hiking, and playing sports (football, basketball, rugby, and more). He also loves working his way through every recipe he can find in the family cookbook or elsewhere, and indulging his love for seeing new places.Krishna Bhavsar has spent around 10 years working on natural language processing, social media analytics, and text mining in various industry domains such as hospitality, banking, healthcare, and more. He has worked on many different NLP libraries such as Stanford CoreNLP, IBM's SystemText and BigInsights, GATE, and NLTK to solve industry problems related to textual analysis. He has also worked on analyzing social media responses for popular television shows and popular retail brands and products. He has also published a paper on sentiment analysis augmentation techniques in 2010 NAACL. he recently created an NLP pipeline/toolset and open sourced it for public use. Apart from academics and technology, Krishna has a passion for motorcycles and football. In his free time, he likes to travel and explore. He has gone on pan-India road trips on his motorcycle and backpacking trips across most of the countries in South East Asia and Europe.Naresh Kumar has more than a decade of professional experience in designing, implementing, and running very-large-scale Internet applications in Fortune Top 500 companies. He is a full-stack architect with hands-on experience in domains such as ecommerce, web hosting, healthcare, big data and analytics, data streaming, advertising, and databases. He believes in open source and contributes to it actively. Naresh keeps himself up-to-date with emerging technologies, from Linux systems internals to frontend technologies. He studied in BITS-Pilani, Rajasthan with dual degree in computer science and economics.Pratap Dangeti develops machine learning and deep learning solutions for structured, image, and text data at TCS, in its research and innovation lab in Bangalore. He has acquired a lot of experience in both analytics and data science. He received his master's degree from IIT Bombay in its industrial engineering and operations research program. Pratap is an artificial intelligence enthusiast. When not working, he likes to read about nextgen technologies and innovative methodologies. He is also the author of the book Statistics for Machine Learning by Packt.
