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所在平台: Udemy |
课程主页: https://www.udemy.com/course/natural-language-processing-nlp-with-nltk-and-scikit-learn/
课程评论：没有评论
课程名称：自然语言处理（NLP）与NLTK和Scikit-learn 课程概述：自然语言处理（NLP）是数据科学中最引人入胜的一个子领域，它提供了强大的方法来解释和处理口头及书面语言。NLP的应用包括客户支持问询处理、产品情感分析以及提供直观的用户界面。本课程将帮助你利用NLP构建高性能的日常应用。这个综合的二合一课程教你如何使用流行的数据科学概念NLP编写应用程序。课程开始时，你将构建三个NLP应用：垃圾邮件过滤器、主题分类器和情感分析器。之后，学习如何使用开源库如NLTK、scikit-learn和spaCy来轻松进行日常NLP任务，借助机器学习和NLP处理模型。课程将从基础知识开始，比如使用语料库和正则表达式，逐步学习高级NLP概念，同时解决日常工作中的常见NLP问题，通过实际演示、清晰解释和有趣的真实世界例子来加深理解。 培训计划包含两门完整的课程，旨在为你提供最全面的培训。第一门课程“使用NLTK和Scikit-learn的实践NLP”将让你直接上手，在第一个视频中建立垃圾邮件分类器。你还将构建三个NLP应用：垃圾邮件过滤器、主题分类器和情感分析器，能轻松构建实际的解决方案。第二门课程“使用Python中的NLTK开发NLP应用”针对高级解决方案，助你从初学者变为自然语言处理的专家，内容涵盖自然语言理解、处理及句法分析，结合了高效使用NLTK实施文本分类、识别词性、标记词汇等必要知识。 通过完成此学习路径，你将能够使用Python与NLP创建新应用，并能轻松构建实际的基于机器学习和NLP处理模型的解决方案。 专家介绍：该课程由Colibri Ltd的技术顾问团队设计，此公司专注于大数据、数据科学、机器学习和云计算，帮助企业更智能地处理数据。此外，Rudy Lai、Krishna Bhavsar、Naresh Kumar和Pratap Dangeti等专家也参与了课程的内容设计，他们在NLP、机器学习以及相关技术领域拥有丰富经验。 通过这个课程，你将获得多样化的NLP技能，并能将其应用于自己的开发项目中。
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 Learning Path.This comprehensive 2-in-1 course teaches you to write applications using one of the popular data science concept, NLP. You will begin with building 3 NLP applications which are a spam filter, a topic classifier, and a sentiment analyzer. You will then learn how to use open source libraries such as NLTK, scikit-learn, and spaCy to perform routine NLP tasks backed by machine learning and NLP processing models with ease. You will be taken on a journey starting from the very basics such as using a corpus and regular expressions to learning advanced NLP concepts while simultaneously solving common NLP problems faced in your day-to-day tasks. You will learn all of these through practical demonstrations, clear explanations, and interesting real-world examples. This learning path will give you a versatile range of NLP skills, which you will put to work in your own applications.This training program includes 2 complete courses, carefully chosen to give you the most comprehensive training possible.The first course, Hands-on NLP with NLTK and Scikit-learn, puts you right on the spot, starting off with building a spam classifier in our first video. You will then build three NLP applications: a spam filter, a topic classifier, and a sentiment analyzer. You will also be able to build actual solutions backed by machine learning and NLP processing models with ease.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 Learning Path, you will be able to create new applications with Python and NLP. You will also be able to build actual solutions backed by machine learning and NLP processing models with ease. Meet Your Expert(s):We have the best work of the following esteemed author(s) to ensure that your learning journey is smooth:Colibri Ltd is a technology consultancy company founded in 2015 by James Cross and Ingrid Funie. The company works to help its clients navigate the rapidly changing and complex world of emerging technologies, with deep expertise in areas such as big data, data science, machine learning, and cloud computing. Over the past few years, they have worked with some of the world's largest and most prestigious companies, including a tier 1 investment bank, a leading management consultancy group, and one of the World's most popular soft drinks companies, helping each of them to make better sense of its data, and process it in more intelligent ways. The company lives by its motto: Data -> Intelligence -> Action.Rudy Lai is the founder of QuantCopy, a sales acceleration startup using AI to write sales emails to prospects. By taking in leads from your pipelines, QuantCopy researches them online and generates sales emails from that data. It also has a suite of email automation tools to schedule, send, and track email performance-key analytics that all feedback into how our AI generated content. Prior to founding QuantCopy, Rudy ran HighDimension.IO, a machine learning consultancy, where he experienced first-hand the frustrations of outbound sales and prospecting. As a founding partner, he helped startups and enterprises with High Dimension. IO's Machine-Learning-as-a-Service, allowing them to scale up data expertise in the blink of an eye. In the first part of his career, Rudy spent 5+ years in quantitative trading at leading investment banks such as Morgan Stanley. This valuable experience allowed him to witness the power of data, but also the pitfalls of automation using data science and machine learning. Quantitative trading was also a great platform from which to learn deeply about reinforcement learning and supervised learning topics in a commercial setting.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.
