--- title: NLTK Reviews meta_title: 'NLTK Reviews 2026: Details, Pricing, & Features | G2' meta_description: Filter 48 reviews by the users' company size, role or industry to find out how NLTK works for a business like yours. aggregate_rating: rating_value: 4.4 review_count: 48 scale: '5' date_modified: '2026-08-09' parent_category: name: Natural Language Processing (NLP) url: https://www.g2.com/categories/natural-language-processing-nlp --- # NLTK Reviews **Vendor:** NLTK Project **Category:** [Natural Language Understanding (NLU) Software](https://www.g2.com/categories/natural-language-understanding-nlu) **Average Rating:** 4.4/5.0 **Total Reviews:** 48 ## About NLTK NLTK is a platform for building Python programs to work with human language data that provides interfaces to corpora and lexical resources such as WordNet, along with a suite of text processing libraries for classification, tokenization, stemming, tagging, parsing, and semantic reasoning, wrappers for industrial-strength NLP libraries, and an active discussion forum. ## NLTK Reviews ### 1. Beast in language processing **Rating:** 4.5/5.0 stars **Reviewed by:** Verified User in Telecommunications | Mid-Market (51-1000 emp.) **Reviewed Date:** July 22, 2022 **What do you like best about NLTK?** Nltk simply breakdown a paragraph into sentences and then sentences into words. This is the key and I liked it very much personally. **What do you dislike about NLTK?** Yes everything has some things which can be better . Now audience have multiple choices so competition is high.comaparing with spacy it could be improve. **What problems is NLTK solving and how is that benefiting you?** It's a library. and we can integrate it in our projects to simply paragraphs , splitting the data and accordingly your selected language. ### 2. NLTK - A useful toolkit to start with NLP **Rating:** 4.0/5.0 stars **Reviewed by:** Deepanshu D. | Software Engineer, Small-Business (50 or fewer emp.) **Reviewed Date:** May 20, 2022 **What do you like best about NLTK?** I've been working with Python for a long time, and this toolkit has made things a lot simpler. The features contained in the libraries are simple to use and make working with Python more fluid and painless. **What do you dislike about NLTK?** I believe it still lacks a number of functionalities that other competitors have included compared to NLTK. They need to upgrade themselves quickly or they might get left behind in the race. **What problems is NLTK solving and how is that benefiting you?** It has added more support for NLP and made it more powerful by integrating third-party libraries. The main issue it has fixed for me is text processing. ### 3. I have used NLTK extensively to ace Machine Learning Hackathons **Rating:** 4.0/5.0 stars **Reviewed by:** Pratik N. | Technical Writer, Small-Business (50 or fewer emp.) **Reviewed Date:** December 01, 2020 **What do you like best about NLTK?** NLTK has plethora of tools to clean and pre-process your text data. I cannot imagine how many hours it would take to sit and manually clean the text data if it wasn't the amazing in-built of NLTK. I would say NLTK has made life of Data Scientists easy. **What do you dislike about NLTK?** Some of the functionalities like Lemmatization is pretty slow when corpus size is large. So, I have to adjust with stemming. Also, spelling correction functionality doesn't perform that well for SMS language. It would be amazing if the support is extended to identify the words in their short-form. **Recommendations to others considering NLTK:** NLTK is a great tool for Natural Language Processing tasks. The documentation provided is easy to understand with ample of examples. I would certainly recommend it to the beginners who are starting with their Machine Learning journey, as well as the experienced folks in ML industry. **What problems is NLTK solving and how is that benefiting you?** I have used this library primarily for text cleaning in the pre-processing stage and feature extraction before building ML model. While working on Hackathon problems, I tend to experiment with various functionalities of NLTK toolkit for effective processing of the text data. The best part is most of these tools offered by NLTK is quiet easy to implement, mostly can be achieved with a single line of code. Whenever I am stuck, I refer the official NLTK website and public forums and I always able to find the workaround. ### 4. Function rich and easy to use library....!! **Rating:** 5.0/5.0 stars **Reviewed by:** MAYANK S. | Software Engineer, Mid-Market (51-1000 emp.) **Reviewed Date:** May 27, 2022 **What do you like best about NLTK?** - Tokenizers are one of the best and new things which I have seen for correcting content, I haven't seen this support in any other language. **What do you dislike about NLTK?** - For some functions the accuracy is not so good, so minor handling is needed to be done from your end. **What problems is NLTK solving and how is that benefiting you?** - I use it for reading data from a webhook call and figuring out the keywords after parsing using NLTK. Storing these keywords in MongoDB later using them for targeting and analysing. ### 5. Single Library for multiple use case **Rating:** 5.0/5.0 stars **Reviewed by:** Richa N. | Business Analyst, Small-Business (50 or fewer emp.) **Reviewed Date:** June 01, 2022 **What do you like best about NLTK?** As a data scientist NlTK reduces my over head of using multiple library for some preprocessing steps **What do you dislike about NLTK?** Nothing to dislike, just I had to get familiar with the library as it is the case with any other library to make the use easy and know what to use where. **What problems is NLTK solving and how is that benefiting you?** I used it when I was working for my fiver client in an image recognition project to preprocess and get sample test cases. ### 6. Natural Language ToolKit **Rating:** 4.0/5.0 stars **Reviewed by:** Harshit A. | DevOps Engineer, Mid-Market (51-1000 emp.) **Reviewed Date:** July 05, 2022 **What do you like best about NLTK?** Natural Language Processing with Python provides a practical implementation to programming for language processing and we can use with datascience and ml platform for its advance uses **What do you dislike about NLTK?** If your algo is not best then it will impact nltk process. **What problems is NLTK solving and how is that benefiting you?** Its solving out language proceaaing problem that we have faced before python comes in phase. ### 7. Package with high utility **Rating:** 5.0/5.0 stars **Reviewed by:** Harshit P. | Software Engineer (IC2), Small-Business (50 or fewer emp.) **Reviewed Date:** May 31, 2022 **What do you like best about NLTK?** NLTK includes lot of features for which earlier I was using different library for each feature like tokenization etc. **What do you dislike about NLTK?** There is nothing as such I dislike about NLTk but there is lack of resources to tell the wide use case in which NLTK can be used. **What problems is NLTK solving and how is that benefiting you?** I used it in my deep learning project where I needed NLTK for some preprocessing like tokenization , parking striling etc. ### 8. NLTK: the go to for Natural Language Processing in python **Rating:** 4.0/5.0 stars **Reviewed by:** Claudio M. | Data Scientist, Enterprise (> 1000 emp.) **Reviewed Date:** November 24, 2020 **What do you like best about NLTK?** I really like the overall NLTK's API. I often use the whole pre processing pipeline related API's , I also use TextCat for language identification. I also like the pos-tagging API's and the sentiment analysis one . **What do you dislike about NLTK?** It would be awesome if API's were a little bit faster since by reading some stack overflow answers, I sometimes found users replying to questions presenting some speed benchmarks comparing NLTK's speed with other NLP related libraries and showing it didn't was the fastest one among them . **Recommendations to others considering NLTK:** I recommend the use of NTLK everytime you have to deal with text and you have to perform every type of natural language processing related analysis. It offers easy APIs to deal with every language. You can leverage wordnet api's to calculate synsets distances and related measures. It supports also part of speech tagging , machine translation , dependency parsing and sentiment analysis API's. You can also use neural networks for some specific tasks . **What problems is NLTK solving and how is that benefiting you?** I'm dealing with general natural language processing tasks , such as text mining , text classification and topic modeling. I used nltk textcat to identify and split my data according to detected languages . Then the whole pre processing pipeline was implemented in NLTK. I used wordnet api in order to instantiate a wordnet lemmatizer and used it in conjuction with the pos tag api in order to use lemmatization enriched by pos tagging . ### 9. Nltk: A library for text processing in python **Rating:** 4.0/5.0 stars **Reviewed by:** Alvaro R. | Profesor titular, Enterprise (> 1000 emp.) **Reviewed Date:** October 13, 2020 **What do you like best about NLTK?** Nltk offers differents types of analysis as lemmatization, pos tagging, stop words removal, etc **What do you dislike about NLTK?** The kind of processing may differ depending on the language. Besides, the coverage of applications for each language is different. **Recommendations to others considering NLTK:** Before using nltk, you should check if all the functionalities required for you are available for your language. The language with most applications is English, so you need to know if you can apply similar processing in your language. On the other hand, the way of calling to some functionalities depends on the language because some models are more effective for some language than for another. I also recommend checking the performance of the functionality you want to use. That is, as it is already known in natural language processing, the precision in some tasks is close to 100, while in others it is lower. **What problems is NLTK solving and how is that benefiting you?** I have used nltk to apply previous processing to input texts. For example, nltk helps me to remove stop words, in any language, as well as obtaining lemmans and stems from every word. Besides, I can used also ntlk for name entity recognition in several languages. Thus, I can obtain several features from a single text. One of the main benefits of using nltk is the fact that the processing is quite fast. Moreover, I like the fact that I can find lots of information on the Internet, with several examples. This helps me a lot when I want to process texts using nltk. ### 10. NLTK is very handy for NLP pipelines ! **Rating:** 4.0/5.0 stars **Reviewed by:** M C. | Business Analyst, Enterprise (> 1000 emp.) **Reviewed Date:** December 28, 2020 **What do you like best about NLTK?** The best thing about NLTK is its ease of implementation. Without it to write algorithms from scratch it take ages but it helps in quick prototyping. Another thing that is great about NLTK is it has great pre trained models and corpus of data which makes text processing and analysis pretty quick and easy. **What do you dislike about NLTK?** There is not much to dislike about NLTK but ya it has improved a lot in time. I would like it to more fine tune its algorithms as some of its competitor like SpaCy is doing. It only works syntactically and i would prefer if in future looks into semantic aspect of text as well. Another thing it misses are the neural network models as it has no deep learning capabilities. **Recommendations to others considering NLTK:** Yes I would totally recommend NLTK for others want to get into natural language processing as it is fairly easy to setup and learn. **What problems is NLTK solving and how is that benefiting you?** The main benefit I have realized is quick prototyping with help of NLTK. It helps me to give actual shape to my projects in no time. Another benefit for NLTK is it is very easy and quick to learn so that I can bring my whole team in same page very fast and that really helps in quick research and development. ### 11. Good Start for NLP Techniques **Rating:** 4.0/5.0 stars **Reviewed by:** Ridhima g. | Data Scientist, Small-Business (50 or fewer emp.) **Reviewed Date:** November 27, 2020 **What do you like best about NLTK?** It is the best package for processing and understanding the text in less coding. It provides so many functionalities such as tokenization, chunking, chinking in text processing, dependency parsing in understanding the text. Documentation is easily available and fully open source. **What do you dislike about NLTK?** You have to download the desired collection such as you want to use wordnet then before using downloading is necessary. **Recommendations to others considering NLTK:** Spacy is also one of the good packages for processing and performing NLP task **What problems is NLTK solving and how is that benefiting you?** I used NLTK majorly for pre-processing in Natural Language Processing tasks such as review classification then each review is in the raw form. Hence we have to perform processing and make it a useful vector. Perfect library for basic processing on the text like stop-word removal, tokenization, etc. ### 12. Great experience with NLTK **Rating:** 4.0/5.0 stars **Reviewed by:** Marcelo Q. | Data Scientist, Enterprise (> 1000 emp.) **Reviewed Date:** December 03, 2020 **What do you like best about NLTK?** NLTK is easy to use and pretty effective. It also has good documentation and a lot of people using stack overflow to ask and answer questions about it - for a dev, is always important. **What do you dislike about NLTK?** I have no major things I don't dislike but It will be good to add more higher level functions, allowing devs to do more with less code. **Recommendations to others considering NLTK:** It is easy to search text analysis solutions using NLTK. **What problems is NLTK solving and how is that benefiting you?** Predictive projects, mostly, where I had also text analysis to do. One of the projects I can mentione is a financial analysis in the 10-K reports of the major companies in the US. I extracted text complexity indicatores and correlated it with profit. ### 13. Easiest way to understand natural language with Python! **Rating:** 4.5/5.0 stars **Reviewed by:** Faustina Maria G. | Data Science Fellow, Mid-Market (51-1000 emp.) **Reviewed Date:** November 30, 2020 **What do you like best about NLTK?** Using it was fun! It's one of the most complete libraries in Python for NLP. If you want to start a project right away, NLTK is the way to go. It has everything you need to do it, and you may not need to import any other libraries, except you're looking for more complex algorithms. In my case, I've worked almost exclusively with NLTK and didn't need any other libraries. I liked how easy it was to start getting things done with it. **What do you dislike about NLTK?** Importing submodules can be a little bit tricky, the documentation doesn't provide clear information about them. Also, the docs could be clearer and have less versions only, since you get lost trying to match the version with those only to make sure that the cases apply to yours. I was discouraged by how intricate the docs were. Fortunately, many people choose to use it, so I found snippets and repos, and other materials with use cases similar to mine. If you enjoy sleuthing, this is your tool. **What problems is NLTK solving and how is that benefiting you?** Recommendation engine for an NGO looking to provide free psychological advice for minor cases during the pandemic. The project was done majorly on NLTK, I didn't need much from other libraries because the basics and more were provided by the library. ### 14. Fast learning curve plus the full set of tools **Rating:** 5.0/5.0 stars **Reviewed by:** Ali M. | Senior Machine Learning Engineer, Small-Business (50 or fewer emp.) **Reviewed Date:** November 30, 2020 **What do you like best about NLTK?** NLTK is a collection of most of the tools required for NLP. It is easy to learn and well documented. I appreciate its license Apache 2.0 which permits the usage for commercial purposes. At the time I used it I was quite beginner in the field. Using NLTK allowed me to dive straight into the project while learning the toolkit. Its word tokenizer tools are pretty easy to use. I pretty much like NLTK as a preprocessing tool for my deep learning pipelines. **What do you dislike about NLTK?** I would have seen more examples in the documentation. Probably adding several notebooks on the github page could be very useful. Another thing bothers me is that the developer team in Github are not that responsive. What mentioned above are pretty much look like wishes rather than dislikes. **Recommendations to others considering NLTK:** They first need to figure out what exactly they need from NLTK. Going through the documentation from A-Z is not the best approach. They can start off with a simple tutorial then handpick their topics while implementing their project. The tool is quite useful in combination with deep learning frameworks such as tensor-flow or pytorch. One can use NLTK to pre-process the training data. I personally used it tokenize my text. I also used the word2vec feature to transform my data into embeddings. In Kaggle there are lots of projects which used NLTK. It is definitely a great resource to get familiar with the toolkit and its potentials in the form of real world projects. For questions, there are a considerable amount of stack overflow threads, which I benefited a lot. **What problems is NLTK solving and how is that benefiting you?** The aim was to develop a pipeline to classify jobs by their descriptions. I used it to convert my data to embeddings. It was quite handy. At that time I was quite beginner in the field and needed an easy to use package, so I decided to use Nltk. I also used the tool while I was learning deep learning in Udacity. The project was a sentiment analysis and NLTK turned out to be quite useful. In particular I used it to tokenize my data and then fed them to a pytorch pipeline. ### 15. A Swiss army knife to build chatbots, text mining, sentimental analysis and NLP applications **Rating:** 5.0/5.0 stars **Reviewed by:** Habben I. | Mid-Market (51-1000 emp.) **Reviewed Date:** December 07, 2020 **What do you like best about NLTK?** it makes it easy to create sentimental analysis on text data, write grammar rules for chatbots, tokenization, NER, tagging and entity recognition while being open source with it's fast fast learning curve. When it comes to fast prototyping of the NLP related projects or apps, NLTK is second to none in this regard. **What do you dislike about NLTK?** I would like to train it on custom dataset and a bit more detailed code examples. **What problems is NLTK solving and how is that benefiting you?** Building sentimental analysis tools, customer support chatbots and helping the special people perform actions from simple commands, clustering the client feedback. We also have experimental tools which can help in classifying the texts from people which show high stress. ### 16. NLTK is good tool for college students to learn basics **Rating:** 3.5/5.0 stars **Reviewed by:** Shahid H. | Data Scientist, Small-Business (50 or fewer emp.) **Reviewed Date:** November 26, 2020 **What do you like best about NLTK?** NLTK is easy to learn at the start. It is widely accepted in colleges and universities to teach new students the basics of NLP. NLTK offers basics of NLP and also you can integrate with gensim models for language modeling which I think is upside of NLTK. Researchers use NLTK because it offers basics of NLP. Sentence parser is fast but sometime breaks at wrong position. **What do you dislike about NLTK?** NLTK doesn't offer some things that its competitors do. For example word parser of NLTK is slow as compared to spacy. Spacy returns object which can easily used in further operations while NLTK returns string. POS tagging is very slow and same for NER. In industry, Spacy is widely used. **Recommendations to others considering NLTK:** New researcher in NLP and new students can use NLTK to learn the basics of NLP. I would recommend using Gensim and wordnet with NLTK. It would enhance your experience. **What problems is NLTK solving and how is that benefiting you?** I have used it in start of my career and in university to learn basics. I have used it for word/sentence similarity using gensim models. ### 17. Junior Data Scientist **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Information Technology and Services | Small-Business (50 or fewer emp.) **Reviewed Date:** December 06, 2020 **What do you like best about NLTK?** I find NLTL less complicated as most of the pre processing required for the text data are readily available that can be used directly without any modification required. It does include all the basic functions required to clean the data when working with AI **What do you dislike about NLTK?** I would not put it as dislike but as and when more things like spacy have come up NLTK scores little down . For all the basic computations its an ease may be little slow when compared to other libraries and quite not accurately updated with the flow AI is moving **Recommendations to others considering NLTK:** YEs I would definitely recommend beginners to use NLTK ,this is the first thing that pops up when working on a NLP project. Its like a go to library to start with a project .due to its simplicity I would always like to try with NLTK and only if something dose not work with this then I would prefer or research about other libraries **What problems is NLTK solving and how is that benefiting you?** Sometimes gets slow while downloading the functions , and things like categorizing the data is not well done . Benefit is the simplicity in the usage ### 18. NLTK - A powerful NLP library **Rating:** 5.0/5.0 stars **Reviewed by:** Nikhil B. | Machine Learning Engineer, Small-Business (50 or fewer emp.) **Reviewed Date:** December 09, 2020 **What do you like best about NLTK?** determining polarity of the sentence is the most powerful feature of NLTK. Among those detecting NER, designing your own pipeline are also one of the best features of NLTK library **What do you dislike about NLTK?** I won't say dislike but NLTK is a little bit slower in speed performance from other libraries such as spacy. **What problems is NLTK solving and how is that benefiting you?** I made an IELTS written exam checking system using NLTK and python it used various algorithms of relativelity of student's answer to question asked, tone of the answer written, how correlated the sentences of answer are, mood and sentiment of answer and various other factors on which the asnwer depends like grammer, sentence construction(simple,compound, complex), punctualtion etc. ### 19. Senior Machine Learning Engineer with 4+ years of experience **Rating:** 4.0/5.0 stars **Reviewed by:** Uridah S. | Senior Machine Learning Engineer, Small-Business (50 or fewer emp.) **Reviewed Date:** December 01, 2020 **What do you like best about NLTK?** I work mostly in python. I know it is available for a number of languages but I will review only for python. It provides a variety of features from tokenization to stemming and lemmatization. Having these basic features allow you to get basic NLP tasks without having to do anything complicated. Another pro of NLTK is that it is really easy to use and you can get started right away. **What do you dislike about NLTK?** It doesn't provide any advanced features and lack of neural networks affect its performance where sometimes it makes mistake when lemmatizing and stemming very basic words. **What problems is NLTK solving and how is that benefiting you?** I always use NLTK in combination with other libraries. ### 20. Review of NLTK **Rating:** 4.0/5.0 stars **Reviewed by:** Hassan J. | Sr Machine Learning Engineer, Small-Business (50 or fewer emp.) **Reviewed Date:** December 10, 2020 **What do you like best about NLTK?** Over all NLTK serves quite well for my use case. It helps with NLP pipelines. NLTK has a very good stop words corpus as well. I have also used NLTK for intent detection and the results were quite satisfactory given the small dataset we used **What do you dislike about NLTK?** NLTK is kinda slow. There should performance improvement both when it comes to time and memory usage. Also with introduction of more advance language models, maybe NLTk should also incorporate some more deep nueral network models **What problems is NLTK solving and how is that benefiting you?** Using NLTK for Stop Words For Intent Detection Also used in combination with Spacy for NER ### 21. A comprehensive guide to NLTK in python with practical examples and complete code **Rating:** 4.5/5.0 stars **Reviewed by:** Ali R. | Senior Full Stack Python and PHP Developer, Small-Business (50 or fewer emp.) **Reviewed Date:** November 30, 2020 **What do you like best about NLTK?** The best thing about NLTK is, it provides the practical solution to the NLP topics which cannot just be explained with theory only. **What do you dislike about NLTK?** I couldn't find any downsides in the book, but would like to have more coding examples. **What problems is NLTK solving and how is that benefiting you?** I mainly work in chat bots and user support where we use the NLTK to cover a wide variety of tasks, including replies to customer emails, live chat, replies to customer queries sent via social media messaging platforms. The best part of NLTK is having well documented codebase and easier to configure and customise when using in our own solutions ### 22. powerfull tool for text analysis **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Higher Education | Mid-Market (51-1000 emp.) **Reviewed Date:** November 29, 2020 **What do you like best about NLTK?** With NLTK was super useful in carrying out a sentiment analysis on movie reviews, furthermore, the corpora present in NLTK are useful in carrying out comparisons for text analysis. Features that I found extremely useful are all the helping function present for tokenization of the text. **What do you dislike about NLTK?** It would be nice to automatically generate graphs since for word distribution there is a little tinkering to do to make the graph look good. But overall not much to complain about. **What problems is NLTK solving and how is that benefiting you?** Text analysis and sentiment analysis. Great overview of the text with easy steps. ### 23. For me it's a Backbone for NLP Applications, going stronger day by day. **Rating:** 5.0/5.0 stars **Reviewed by:** Anmol D. | Sr. Machine Learning Engineer, Mid-Market (51-1000 emp.) **Reviewed Date:** December 03, 2020 **What do you like best about NLTK?** This library has tools for almost all NLP tasks with many 3rd party extensions. **What do you dislike about NLTK?** Preprocessing layer can be improved by adding analysis upon semantic structure. **What problems is NLTK solving and how is that benefiting you?** I use NLTK majorly for my pre-processing, it provides plenty of approaches to each NLP task, fastest framework and support many languages. ### 24. Wonderful tool for NLP **Rating:** 4.0/5.0 stars **Reviewed by:** Ali R. | Software Engineer, Small-Business (50 or fewer emp.) **Reviewed Date:** January 28, 2021 **What do you like best about NLTK?** It is easy as described in documentation and very dominant tool when it comes to text cleaning and processing. **What do you dislike about NLTK?** I do not think, there is anything to be dislike. **Recommendations to others considering NLTK:** Recommended for Natural Language Processing task. **What problems is NLTK solving and how is that benefiting you?** The problems i used to solve with NLTK is text processing. It helps me a lot. ### 25. Most easy and Powerful library for natural language processing **Rating:** 4.5/5.0 stars **Reviewed by:** Mouli C. | Data Scientist at GTS Labs, Enterprise (> 1000 emp.) **Reviewed Date:** December 15, 2020 **What do you like best about NLTK?** Its friendly and easy to use support and lots of documentation about all supported functions **What do you dislike about NLTK?** scalability not yet supported and training my own model bit difficult **What problems is NLTK solving and how is that benefiting you?** I have used NLTK for mostly for all my text preprocessing stuff and due to the limitation of creating my own model is not fully available with scalability we have not touched that part yet, but how ever for all preprocessing stuff its the best to use. ### 26. I use NLTK to build chatbot and make conversational dialogue system. **Rating:** 5.0/5.0 stars **Reviewed by:** sushant s. | Deep Learning Engineer | Computer Vision Developer, Small-Business (50 or fewer emp.) **Reviewed Date:** November 24, 2020 **What do you like best about NLTK?** It is easy to use. Efficient use with python.It consists all the package need to build NLP system **What do you dislike about NLTK?** NLTK not support efficient implementation as of Spacy. So, it needs more function to it. **Recommendations to others considering NLTK:** NLTK is good for beginners with it's ease of use, consists different operation support which is needed to build NLP system. **What problems is NLTK solving and how is that benefiting you?** Preprocessing text like tokenization, lemmatization, sentence parsing and other task can be easily perform with nltk. Chatbot, language translation, speech recognition problems I am solving with nltk. ### 27. Had a wonderful experience with NLTK **Rating:** 4.0/5.0 stars **Reviewed by:** Shaheer R. | Software Engineer, Mid-Market (51-1000 emp.) **Reviewed Date:** December 30, 2020 **What do you like best about NLTK?** It is very handy to understand and for searching and analysis with easy documentation. **What do you dislike about NLTK?** Nothing to dislike but it contains only basic functionalities but hope it includes much more in the future. **What problems is NLTK solving and how is that benefiting you?** I frequently used NLTK for the data to embedding conversion and it came out very useful and amazing. I also used it with leaning deep learning libraries with sentiment analysis. ### 28. Extremely helpful **Rating:** 4.5/5.0 stars **Reviewed by:** Priyanka B. | Member of Google Developer Community, Small-Business (50 or fewer emp.) **Reviewed Date:** December 04, 2020 **What do you like best about NLTK?** Using NLTK for text analysis made my job of pre-processing much easier. NLTK has helped building other features on it like TextBlob. Recommendation system and sentiment analysis are two major parts of text analysis which have advanced a lot with introduction and usage of NLTK. **What do you dislike about NLTK?** A bit slow and only splits text by sentences, without analyzing the semantic structure. **What problems is NLTK solving and how is that benefiting you?** Recommendation system, Sentiment analysis and supports the largest number of languages compared to other libraries. ### 29. The grand-old-man of Natural Language Processing **Rating:** 4.0/5.0 stars **Reviewed by:** Siddhant S. | Data Scientist, Enterprise (> 1000 emp.) **Reviewed Date:** December 01, 2020 **What do you like best about NLTK?** Easy learning curve, ease of implementation **What do you dislike about NLTK?** Slow compared to newer NLP frameworks like SpaCy and Gensim **What problems is NLTK solving and how is that benefiting you?** Text preprocessing for classification, named entity recognition. Very easy to learn and prototype compared to other frameworks. ### 30. A go to Library for unstructured text **Rating:** 5.0/5.0 stars **Reviewed by:** Harsh S. | Machine Learning Engineer, Enterprise (> 1000 emp.) **Reviewed Date:** December 02, 2020 **What do you like best about NLTK?** Tasks like removal of stopwords, tokenization, NER, sentiment analysis are so quick to perform using NLTK. **What do you dislike about NLTK?** No NN models, no semantic structure while splitting sentences **Recommendations to others considering NLTK:** Start off your NLP projects via NLTK. It's quick to learn, easy to implement and quick to give you good enough results **What problems is NLTK solving and how is that benefiting you?** It's very quick and easy for text exploration and cleaning. I start almost all my NLP problems with NLTK as benchmark. ### 31. one of the best library in python for nlp **Rating:** 5.0/5.0 stars **Reviewed by:** Abhishek k. | Software Engineer, Enterprise (> 1000 emp.) **Reviewed Date:** November 24, 2020 **What do you like best about NLTK?** part of speech tagging and entity recognization is one of the best feature **What do you dislike about NLTK?** Not able to train the nltk on my own data **What problems is NLTK solving and how is that benefiting you?** Entity recognization for information extraction on pdf and text documents ### 32. Ntlk is a wonderful tool for anyone doing natural language processing from beginner to experts. **Rating:** 4.5/5.0 stars **Reviewed by:** Jabir M. | Small-Business (50 or fewer emp.) **Reviewed Date:** December 02, 2020 **What do you like best about NLTK?** Functions work seamlessly and quickly regardless of the size of the datasets. **What do you dislike about NLTK?** It does not come with a Part of Speech Tagger. **What problems is NLTK solving and how is that benefiting you?** I used nltk to do topic modelling on newspaper article to extract the news story the article is discussing. Nltk was very helpful in perform tasks like tokenzations and calcualting td-idf scores. ### 33. This is the ship that is going to save in the middle of text ocean. **Rating:** 4.5/5.0 stars **Reviewed by:** Sri Ganesh T. | Data Scientist, Small-Business (50 or fewer emp.) **Reviewed Date:** December 01, 2020 **What do you like best about NLTK?** Pythonic way of dealing text data. Very easy to understand and work with. Good documentation and support. **What do you dislike about NLTK?** Haven't find any downsides, can be improved in finding regex. **Recommendations to others considering NLTK:** NLTK is easy to learn and have implemented many functions related to text processing. **What problems is NLTK solving and how is that benefiting you?** For every text preprocessing NLTK is my go to library. ### 34. The NLTK (Natural Language Toolkit) Library is a suite of libraries and programs for symbolic and statistical natural language processing for English written in the Python programming language. **Rating:** 5.0/5.0 stars **Reviewed by:** Sumanth M. | Data Scientist, Enterprise (> 1000 emp.) **Reviewed Date:** November 24, 2020 **What do you like best about NLTK?** Handige functies voor het voorbewerken van tekst. Diepgaande kennis over het nltk-pakket. Geweldige ondersteuning van de gemeenschap. Ondersteunt verschillende talen. **What do you dislike about NLTK?** Recent advancements in NLP are not present. Also, changes in the corpus affect the function output. **What problems is NLTK solving and how is that benefiting you?** I used the nltk package to build chatbots for retail and banking clients. ### 35. Amazing book for beginners **Rating:** 4.5/5.0 stars **Reviewed by:** Kumar S. | Enterprise (> 1000 emp.) **Reviewed Date:** December 02, 2020 **What do you like best about NLTK?** Book is easy to understand and concepts are given from scratch. **What do you dislike about NLTK?** The code is good but can be explained in more depth. **What problems is NLTK solving and how is that benefiting you?** NLTK is library to solve various NLP problem. I used this library for developing questions and answers system. ### 36. Good book covering most of the important topics **Rating:** 4.0/5.0 stars **Reviewed by:** Mohan K. | Senior Data Scientist, Enterprise (> 1000 emp.) **Reviewed Date:** August 12, 2020 **What do you like best about NLTK?** All the fundamental topics are covered in this book Topics around nltk also covered extensively Go to book when it comes to any natural language processing related coding for python **What do you dislike about NLTK?** I feel the latest technological advancements are not there in this book something like word embedding glove vectors word2vec vectors are missing. deep learning techniques like rnn lstm are missing **Recommendations to others considering NLTK:** Good **What problems is NLTK solving and how is that benefiting you?** We solve many of the NLP problems like text classification text summarisation, text analysis, unsupervised learning from text, extracting the relevant phrases from the text. Understanding key topics from large amount of text ### 37. Book covering most of the topics related to NLTK **Rating:** 4.0/5.0 stars **Reviewed by:** Shaheer R. | Application Engineer, Small-Business (50 or fewer emp.) **Reviewed Date:** November 30, 2020 **What do you like best about NLTK?** All basic topics covered with detailed knowledge and easy to understand. **What do you dislike about NLTK?** I do not think, there is something to be disliked. **What problems is NLTK solving and how is that benefiting you?** We are using for our machine learning program to process text. It really helped a lot. ### 38. Good for knowing general NLP **Rating:** 4.0/5.0 stars **Reviewed by:** Peng (Eric) Y. | Project Manager, Small-Business (50 or fewer emp.) **Reviewed Date:** December 02, 2020 **What do you like best about NLTK?** The structure of the content is quite clear. **What do you dislike about NLTK?** The detailed content is normally too repeating and it may fail you in detail understanding. **What problems is NLTK solving and how is that benefiting you?** Social listening engine, segment analysis, and text understanding. ### 39. For preprocessing this is my go to library **Rating:** 5.0/5.0 stars **Reviewed by:** Mohammad Huzefa S. | Head Of Technology | Data Scientist, Small-Business (50 or fewer emp.) **Reviewed Date:** November 27, 2020 **What do you like best about NLTK?** All the predefined dictionaries and classes one line to be used **What do you dislike about NLTK?** It could have been faster, sometimes those external downloads consumes a lot of time. **What problems is NLTK solving and how is that benefiting you?** Text classification and analysis ### 40. extensive work on NLP **Rating:** 3.5/5.0 stars **Reviewed by:** Gangadhar D. | Data Scientist, Mid-Market (51-1000 emp.) **Reviewed Date:** November 30, 2020 **What do you like best about NLTK?** Rich library and easy to handle working examples for better understanding **What do you dislike about NLTK?** mathematical explanations behind examples would be helpful **What problems is NLTK solving and how is that benefiting you?** POS tagging Embedding Semantic understanding ### 41. Great library for natural language processing **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Education Management | Small-Business (50 or fewer emp.) **Reviewed Date:** November 24, 2020 **What do you like best about NLTK?** NLTK contains all the preprocessing models, feature extraction and language models out of the box **What do you dislike about NLTK?** Deep learning support is not available in NLTK **What problems is NLTK solving and how is that benefiting you?** Using NLTK i have created sentiment analysis models, language understanding models and preprocess the text data and extract meaning out of text ### 42. NLTK is used basically in Chatbots, Text Mining, Sentimental Analysis and Language Translation. **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Management Consulting | Small-Business (50 or fewer emp.) **Reviewed Date:** November 30, 2020 **What do you like best about NLTK?** NLTK is the for NLP related projects and has all the solution like Chatbots, Stemming, Text Mining and NLP modelling. **What do you dislike about NLTK?** Nothing to dislike about. Has all the solutions you required as Data-Scientist or Data-Modeller. **What problems is NLTK solving and how is that benefiting you?** Creating Chatbots, Sentimental Analysis using NLTK ### 43. Very concise yet detailed with workable examples and source code **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Retail | Enterprise (> 1000 emp.) **Reviewed Date:** November 30, 2020 **What do you like best about NLTK?** Detailed explanation of each module and function with examples and source code **What do you dislike about NLTK?** Nothing as such. Nothing I came across.. **What problems is NLTK solving and how is that benefiting you?** Started with sentiment analysis and understanding text corpus. Algorithms mentioned were of great help ### 44. Good book to understand natural language processing in python using nltk package **Rating:** 4.5/5.0 stars **Reviewed by:** Nikhil G. | Part Time Trainer, Small-Business (50 or fewer emp.) **Reviewed Date:** January 15, 2019 **What do you like best about NLTK?** It gives detial knowledge about nltk package of python ,what are packages and corpora (texts) in it for text processing. **What do you dislike about NLTK?** The processing of text is done using corpora . So any change in corpora effects packages function output **What problems is NLTK solving and how is that benefiting you?** I used nltk packages knowledge for buliding chatbot who can understand human emotional sentiment and can process it . ### 45. NLTK - Review **Rating:** 5.0/5.0 stars **Reviewed by:** Monica M. | Software Development Intern, Computer Software, Enterprise (> 1000 emp.) **Reviewed Date:** November 24, 2018 **What do you like best about NLTK?** NLTK is a very comprehensive suite of libraries and programs that suited most of my team and I's needs. Not a steep learning curve. **What do you dislike about NLTK?** None I can think of, to be honest. If there is something you want from JAVA packages, you could try to combine it using Jython. **What problems is NLTK solving and how is that benefiting you?** Data mining projects that I have worked on have all used NLTK because it is comprehensive and easy to use! ### 46. Natural Language Processing Eased **Rating:** 5.0/5.0 stars **Reviewed by:** Riya T. | Senior Software Engineer, Computer Software, Small-Business (50 or fewer emp.) **Reviewed Date:** April 17, 2018 **What do you like best about NLTK?** It is open-source and has almost all Natural Language Processing algorithms available. One can get data from stopwords to wordnets. One can carry out simple tasks like tokenizing to complex tasks like stemming. It has a large community support. Also it supports multiple languages. **What do you dislike about NLTK?** I am using it from long time and it has been my only option while carrying out NLP with Python. I have no dislikes for this great library. **Recommendations to others considering NLTK:** It is easy to learn but still if you want you can follow this tutorial : https://www.youtube.com/watch?v=FLZvOKSCkxY , it has helped me a lot personally. **What problems is NLTK solving and how is that benefiting you?** Carrying out NLP tasks and using same in projects we develop in our organisation. ### 47. NLP for Python users **Rating:** 3.5/5.0 stars **Reviewed by:** Verified User in Leisure, Travel & Tourism | Enterprise (> 1000 emp.) **Reviewed Date:** September 28, 2018 **What do you like best about NLTK?** Great for NLP uses like sentiment analysis and text classification; open source **What do you dislike about NLTK?** There are not a lot of NLP options so I mainly use this one, takes a while to get used to it **What problems is NLTK solving and how is that benefiting you?** Sentiment analysis of text reviews ### 48. Good all around tool. **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Consumer Services | Small-Business (50 or fewer emp.) **Reviewed Date:** December 14, 2017 **What do you like best about NLTK?** NLTK makes it easy for me to create grammar rules in order to find specific structures in my text data. The parsers, corpuses, and taggers that it provide are essential in my ML pipeline. **What do you dislike about NLTK?** Sometimes creating the rules that you want can be a pain, but that's just part of learning the tool. **What problems is NLTK solving and how is that benefiting you?** I'm using NLTK to help preprocess text data in our machine learning pipelines. It has helped to speed up our process tremendously. ## NLTK Discussions - [What is NLTK used for?](https://www.g2.com/discussions/what-is-nltk-used-for) - [View NLTK pricing details and edition comparison](https://www.g2.com/products/nltk/reviews?open_modal_url=%2Fproducts%2Fnltk%2Fwishlists%3Fhost_path%3D%252Fproducts%252Fnltk%252Freviews%26source%3Dsticky_header_pin§ion=pricing&secure%5Bexpires_at%5D=2026-08-09+11%3A36%3A18+-0500&secure%5Bsession_id%5D=643ad029-9cda-424f-a8a1-ee26e88b298e&secure%5Btoken%5D=fe1aec56c60ffcb642ecf15031ecb9b4624643122f3cc63e597903942f745db3&format=llm_user) ## NLTK Features **Additional Functionality** - Tagging - Natural Language Processing - Data Extraction - Multi-Language - Predictive Analytics - Drag & Drop - Speech Recognition - Reporting/Analytics - Data Storage Management - Virtual Personal Assistant (VPA) - AI Copilot - Customer Segmentation - Collaboration Tools - Data Import/Export - Generative AI - For eCommerce - Role-Based Permissions - Customizable Branding - Search/Filter - Monitoring - Document Management - API - Data Visualization - Trend Analysis - Machine Learning - Access Controls/Permissions - Alerts/Escalation - Performance Metrics - Real-Time Data - Third-Party Integrations - Mobile App - Multiple Data Sources - For Sales Teams/Organizations - Sentiment Analysis - Activity Dashboard - Chatbot - Workflow Automation **Algorithm** - Part of Speech Tagging - Summarization - Named Entity Recognition - Sentiment Analysis - Emotion Detection - Language Detection **System** - Data Ingestion & Wrangling - Programming Language Support - Drag and Drop - Pre-Built Algorithms - Customizable Models ## Top NLTK Alternatives - [openNLP](https://www.g2.com/products/opennlp/reviews) - 4.0/5.0 (11 reviews) - [Stanford CoreNLP](https://www.g2.com/products/stanford-corenlp/reviews) - 4.3/5.0 (10 reviews) - [Amazon Comprehend](https://www.g2.com/products/amazon-comprehend/reviews) - 4.3/5.0 (83 reviews)