Companies that use NLTK

Frequently asked questions

What is the source of this data?

Our data is sourced from job postings collected from millions of companies. We monitor these postings on company websites, job boards, and other recruitment platforms. Analyzing job postings provides a reliable method to understand the technologies companies are employing, including their use of internal tools.

How often is the data updated?

We refresh our data daily to ensure you are accessing the most current information available. This frequent updating process guarantees that our insights and intelligence reflect the latest developments and trends within the industry.

What is NLTK?

Natural Language Toolkit (NLTK) is a leading platform for building Python programs to work with human language data. It provides easy-to-use interfaces to over 50 lexical and syntactic corpus readers, making it a powerful tool for natural language processing (NLP) tasks. NLTK offers functionalities for tokenization, parsing, classification, stemming, tagging, and semantic reasoning, catering to diverse NLP requirements.

NLTK falls under the category of Machine Learning Tools, specifically tailored for text and language processing applications. It enables developers and data scientists to apply machine learning algorithms to textual data, facilitating tasks such as sentiment analysis, named entity recognition, text summarization, and more. NLTK plays a crucial role in extracting insights from unstructured text data, which is essential across various industries like healthcare, finance, and marketing.

Founded in the early 2000s by Steven Bird and Edward Loper at the University of Pennsylvania, NLTK emerged as an open-source project aimed at promoting research and development in computational linguistics and NLP. The motivation behind NLTK's creation was to democratize access to tools and resources for analyzing human language, fostering advancements in language technology and research.

As of the latest data, NLTK continues to maintain a significant market share within the Machine Learning Tools category due to its robust features, extensive documentation, and active community support. With the increasing demand for NLP solutions in business applications and academia, NLTK is poised to experience further growth in the foreseeable future, solidifying its position as a cornerstone technology in the field of natural language processing.

How to get an updated list of companies that use NLTK?

You can access an updated list of companies using NLTK by visiting TheirStack.com. Our platform provides a comprehensive database of companies utilizing various technologies and internal tools.

How many customers does NLTK have?

As of now, we have data on 2,570 companies that use NLTK.

Who uses NLTK?

NLTK is used by a diverse range of organizations across various industries, including "Professional Services", "It Services And It Consulting", "It Services And It Consulting", "Financial Services", "It Services And It Consulting", "Technology, Information And Internet", "Technology, Information And Internet", "Technology, Information And Internet". For a comprehensive list of all industries utilizing NLTK, please visit TheirStack.com.

What companies use NLTK?

Some of the companies that use NLTK include PwC, GreenXT, Zyte, FactSet, The GBS Group, Federal Data Systems, Silent Eight, CV Library, NEXLAW PTY LTD, Coeuraj and many more. You can find a complete list of 2,570 companies that use NLTK on TheirStack.com.

In which countries NLTK is used the most?

Based on our data, NLTK is most popular in United States (893 companies), United Kingdom (155 companies), India (147 companies), France (58 companies), Canada (54 companies), Germany (51 companies), Spain (44 companies), Brazil (32 companies), Netherlands (24 companies), Switzerland (20 companies). However, it is used by companies all over the world.

How to find companies that use NLTK?

You can find companies using NLTK by searching for it on TheirStack.com, We track job postings from millions of companies and use them to discover what technologies and internal tools they are using.