Top Rated NLTK Alternatives
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. Review collected by and hosted on G2.com.
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. Review collected by and hosted on G2.com.
47 out of 48 Total Reviews for NLTK
Overall Review Sentiment for NLTK
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Nltk simply breakdown a paragraph into sentences and then sentences into words. This is the key and I liked it very much personally. Review collected by and hosted on G2.com.
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. Review collected by and hosted on G2.com.
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. Review collected by and hosted on G2.com.
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. Review collected by and hosted on G2.com.
- 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. Review collected by and hosted on G2.com.
- For some functions the accuracy is not so good, so minor handling is needed to be done from your end. Review collected by and hosted on G2.com.
As a data scientist NlTK reduces my over head of using multiple library for some preprocessing steps Review collected by and hosted on G2.com.
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. Review collected by and hosted on G2.com.
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 Review collected by and hosted on G2.com.
If your algo is not best then it will impact nltk process. Review collected by and hosted on G2.com.
NLTK includes lot of features for which earlier I was using different library for each feature like tokenization etc. Review collected by and hosted on G2.com.
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. Review collected by and hosted on G2.com.
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 . Review collected by and hosted on G2.com.
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 . Review collected by and hosted on G2.com.
Nltk offers differents types of analysis as lemmatization, pos tagging, stop words removal, etc Review collected by and hosted on G2.com.
The kind of processing may differ depending on the language. Besides, the coverage of applications for each language is different. Review collected by and hosted on G2.com.
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. Review collected by and hosted on G2.com.
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. Review collected by and hosted on G2.com.
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. Review collected by and hosted on G2.com.
You have to download the desired collection such as you want to use wordnet then before using downloading is necessary. Review collected by and hosted on G2.com.
