Natural Language Processing (NLP) has made tremendous strides in the past decade. We now have NLP solutions that are able to converse with humans, write text, and summary content with surprising speed and accuracy. If you’re not familiar with it, NLP is a field of study that focuses on the interaction between computers and human language. It’s a pretty broad topic, and it encompasses things like machine translation, sentiment analysis, and even chatbots. In recent years, open source tools for Natural Language Processing have become increasingly popular.
Check out our infographic on The Conversation and Human Interaction Pattern of AI to learn more about how NLP is transforming business.
We are big fans of using open-source tools whenever possible. Not only do they often cost less (or nothing) than proprietary software, but they also give you the flexibility to customize and adapt them to your specific needs. And when it comes to NLP, there are some amazing open-source tools out there that can help you do some really powerful things.
First up, let’s talk about NLTK. This is a Python library that stands for Natural Language Toolkit. It’s a great tool for beginners who are just getting started with NLP, as it has a ton of resources and tutorials that can help you get up to speed. Plus, it has a ton of pre-built modules that you can use for things like tokenization, stemming, and even machine learning.
Next, there’s Gensim. This is another Python library that’s great for NLP, but it’s more geared towards advanced users. It’s specifically designed for topic modeling and document similarity analysis, which makes it perfect for things like text summarization and recommendation systems.
Then, you have spaCy. This is another Python library that’s quickly becoming a favorite among NLP experts. It’s known for being fast and efficient, and it has a ton of pre-built models for different languages. One of the best things about spaCy is that it has a lot of built-in visualizers that make it easy to understand and interpret the results of your NLP analysis.
Another open-source NLP tool is OpenNLP. This is a Java-based library that’s great for common NLP tasks like tokenization, POS tagging, and named entity recognition. It’s also very customizable, so you can create your own models and adapt it to your specific needs.
CoreNLP is also worth mentioning. This is another Java-based library that’s known for its speed and scalability. It’s been used in a lot of large-scale NLP projects, and it’s a great choice if you’re working on something that needs to process a lot of text data quickly.
The tools mentioned above are just a few examples of some amazing open-source NLP tools that are available to you. Each of them can help you do some truly incredible things with human language. See which ones best fit your needs, your team’s level of experience, and how active the open source community is. Armed with the right knowledge, you’re bound to pick a solution that best fits your needs.
Listen to our AI Today Podcast from our AI Glossary Series to learn more about Conversational Systems, Chatbots, Voice Assistants, Machine Translation.
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