Python的自然语言处理:三合一

自然语言处理是人工智能的一部分，处理人类(自然)语言和计算机之间的交互。

这个综合的3合1培训课程包括独特的视频，这些视频将教您使用NLTK执行自然语言处理的各个方面，NLTK是执行该任务的领先Python平台。浏览自然语言处理中的各种主题，从相关Python库的介绍到应用特定的语言学概念，同时在真实世界示例的帮助下探索文本数据集。
Natural Language Processing with Python: 3-in-1

MP4 |视频:h264，1280×720 |音频:AAC，44.1 KHz，2声道
语言：英语+中英文字幕（云桥网络机译） |时长:4小时 29分钟|大小:1.33 GB 含课程文件

构建解决方案，跟上NLP的新趋势。一个综合培训计划中的三个完整课程

你会学到什么
了解如何使用NLTK在文本上创建频率分布
用Python构建您自己的电影评论情感应用程序
导入、访问外部语料库&探索语料库文件中文本的频率分布
执行标记化、词干化、词条化、拼写纠正、停用词移除等等
构建文本相似性、摘要、情感分析和回指解析等解决方案，以跟上自然语言处理的新趋势

要求
良好的Python知识是必须的

关于作者

Tyler Edwards是一名高级工程师和软件开发人员，拥有十多年在航天、国防和核工业领域开发分析工具的经验。Tyler在使用各种编程语言(Python、C++等)方面经验丰富，他的研究领域包括机器学习、人工智能、工程分析和业务分析。Tyler拥有俄亥俄大学机械工程理学硕士学位。展望未来，Tyler希望在应用数学方面指导学生，并演示如何使用数据收集、分析和后处理来解决难题和改进决策。

Krishna Bhavsar花了大约10年的时间研究自然语言处理、社交媒体分析和文本挖掘。他曾致力于许多不同的NLP库，如Stanford Core NLP、IBM的System Text and Big Insights、GATE和NLTK，以解决与文本分析相关的行业问题。他还在2010年NAACL上发表了一篇关于情感分析增强技术的论文。除了学术，他还热衷于摩托车和足球。在空闲时间，他喜欢旅游和探险。

Naresh Kumar在财富500强公司设计、实施和运行超大规模互联网应用程序方面拥有十多年的专业经验。他是一名全栈架构师，在电子商务、虚拟主机、医疗保健、大数据和分析、数据流、广告和数据库等领域拥有实践经验。他相信开源，并积极为此做出贡献。Naresh使自己与新兴技术保持同步，从Linux系统内部到前端技术。他在拉贾斯坦邦的BITS-Pilani学习，获得了计算机科学和经济学双学位。

Pratap Dangeti在TCS位于班加罗尔的研究和创新实验室为结构化、图像和文本数据开发机器学习和深度学习解决方案。他在分析和数据科学方面积累了丰富的经验。他获得了IIT孟买大学工业工程和运筹学专业的硕士学位。普拉塔普是一名人工智能爱好者。不工作时，他喜欢阅读下一代技术和创新方法。他也是Packt出版的《机器学习统计学》一书的作者。

这门课程是给谁的
希望掌握自然语言处理并希望通过实现NLP使其应用程序更加智能的Python开发人员

Build solutions to get up and speed with new trends in NLP. Three complete courses in one comprehensive training program

What you’ll learn
Discover how to create frequency distributions on your text with NLTK
Build your own movie review sentiment application in Python
Import, access external corpus & explore frequency distribution of the text in corpus file
Perform tokenization, stemming, lemmatization, spelling corrections, stop words removals, and more
Build solutions such as text similarity, summarization, sentiment analysis and anaphora resolution to get up to speed with new trends in NLP

Requirements
Good knowledge of Python is a must

Description
Natural Language Processing is a part of Artificial Intelligence that deals with the interactions between human (natural) languages and computers.

This comprehensive 3-in-1 training course includes unique videos that will teach you various aspects of performing Natural Language Processing with NLTK—the leading Python platform for the task. Go through various topics in Natural Language Processing, ranging from an introduction to the relevant Python libraries to applying specific linguistics concepts while exploring text datasets with the help of real-word examples.

About the Author

Tyler Edwards is a senior engineer and software developer with over a decade of experience creating analysis tools in the space, defense, and nuclear industries. Tyler is experienced using a variety of programming languages (Python, C++, and more), and his research areas include machine learning, artificial intelligence, engineering analysis, and business analytics. Tyler holds a Master of Science degree in Mechanical Engineering from Ohio University. Looking forward, Tyler hopes to mentor students in applied mathematics, and demonstrate how data collection, analysis, and post-processing can be used to solve difficult problems and improve decision making.

Krishna Bhavsar has spent around 10 years working on natural language processing, social media analytics, and text mining. He has worked on many different NLP libraries such as Stanford Core NLP, IBM’s System Text and Big Insights, GATE, and NLTK to solve industry problems related to textual analysis. He has also published a paper on sentiment analysis augmentation techniques in 2010 NAACL. Apart from academics, he has a passion for motorcycles and football. In his free time, he likes to travel and explore.

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 e-commerce, 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 Next-gen technologies and innovative methodologies. He is also the author of the book Statistics for Machine Learning by Packt.

Who this course is for
Python developers who wish to master Natural Language Processing and want to make their applications smarter by implementing NLP