Top NLP Skills, Frameworks, Platforms, and Languages for 2023

Natural language processing (NLP) has been growing in awareness over the last few years, and with the popularity of ChatGPT and GPT-3 in 2022, NLP is now on the top of peoples’ minds when it comes to AI. Developing NLP tools isn’t so straightforward, and requires a lot of background knowledge in machine & deep learning, among others. We looked at over 25,000 job descriptions for jobs related to NLP, and here are the most important skills, frameworks, programming languages, and cloud services that you should know for careers in NLP.

NLP Skills for 2023

These skills are platform agnostic, meaning that employers are looking for specific skillsets, expertise, and workflows. The chart below shows 20 in-demand skills that encompass both NLP fundamentals and broader data science expertise.

NLP Fundamentals

As the chart shows, the most important NLP skills that employers are looking for are NLP fundamentals. This means not necessarily just knowing platforms, but how NLP works as a core skill. Knowing how spaCy works means little if you don’t know how to apply core NLP skills like transformers, classification, linguistics, question answering, sentiment analysis, topic modeling, machine translation, speech recognition, named entity recognition, and others. In a change from last year, there’s also a higher demand for those with data analysis skills as well.

Machine & Deep Learning

Machine learning is the fundamental data science skillset, and deep learning is the foundation for NLP. Having mastery of these two will prove that you know data science and in turn, NLP. Employers are mostly looking to know about working with pre-trained models and transformers.

Research

NLP requires staying current with the latest papers and models. Companies are finding NLP to be one of the best applications of AI regardless of industry. Thus knowing or finding the right models, tools, and frameworks to apply to the many different use cases for NLP requires a strong research focus.

Data Science Fundamentals

Going beyond knowing machine learning as a core skill, knowing programming and computer science basics will show that you have a solid foundation in the field. Computer science, math, statistics, programming, and software development are all skills required in NLP projects.

Cloud Computing, APIs, and Data Engineering

NLP experts don’t go straight into conducting sentiment analysis on their personal laptops. Employers are looking for NLP experts who can handle a bit more of the full stack of data engineering, including how to use APIs, build data pipelines, architect workflow management, and do it all on cloud-based platforms

NLP Platforms and Tools

Going beyond skills and expertise, there are a number of specific platforms, tools, and languages that employers are specifically looking for. The chart below shows what’s hot right now. The list isn’t inclusive, so it’s good to look up new tools and frameworks that will become popular eventually.

Machine Learning Frameworks

Alongside knowing general machine and deep learning, a few frameworks stand out as cores for NLP projects. TensorFlow is desired for its flexibility for ML and neural networks, PyTorch for its ease of use and innate design for NLP, and scikit-learn for classification and clustering. While even knowing one of these is attractive, being flexible and adaptable by knowing all three and more will really pop. In a major shift from last year, PyTorch is now the most in-demand machine learning framework and has been slowly overtaking TensorFlow/Keras as the go-to for ML tasks.

NLP Frameworks

To get more NLP-specific, a few NLP frameworks stand out as must-haves for any NLP professional. NLTK is appreciated for its broader nature, as it’s able to pull the right algorithm for any job. Meanwhile, spaCy is appreciated for its ability to handle multiple languages and its ability to support word vectors. New to the list is Apache OpenNLP, mostly used for common NLP tasks and ease-of-use, CoreNLP for its use in Java, and surprisingly not on last year’s list, HuggingFace transformers for its deep learning architecture.

BERT is still very popular over the past few years and even though the last update from Google was in late 2019 it is still widely deployed. BERT stands out thanks to its strong affinity for question-answering and context-based similarity searches, making it reliable for chatbots and other related applications. BERT even accounts for the context of words, allowing for more accurate results related to respective queries and tasks.

Data Engineering Platforms

Spark is still the leader for data pipelines but other platforms are gaining ground. Data pipelines help the flow of text data, especially for real-time data streaming and cloud-based applications. There’s even a more specific version, Spark NLP, which is a devoted library for language tasks. Spark NLP in particular sees a lot of use in healthcare — a field that has a lot of data, especially with medical records and medicine.

NLP Programming Languages

It shouldn’t be a surprise that Python has a strong lead as a programming language of choice for NLP. Many popular NLP frameworks, such as NLTK and spaCy, are Python-based, so it makes sense to be an expert in the accompanying language. Knowing some SQL is also essential. Java has numerous libraries designed for the language, including CoreNLP, OpenNLP, and others.

NLP Cloud Platforms

Cloud-based services are the norm in 2022, this leads to a few service providers becoming increasingly popular. AWS Cloud, Azure Cloud, and others are all compatible with many other frameworks and languages, making them necessary for any NLP skill set. Google Cloud is starting to make a name for itself as well.

Get started with NLP for data science and add it to your skillset at ODSC East 2023

If you’re looking to add an in-demand, evergreen, and broad-use skill to your repertoire, then maybe it’s time to learn about NLP or other core data science skills. At ODSC East 2023, we’ll have an entire mini bootcamp track where you can start with core beginner skills and work your way up to more advanced data science skills, such as working with deep learning or neural networks. ODSC East will also feature an NLP track, specifically designed to teach core NLP skills and platforms. We also have plenty of NLP sessions available on-demand on the Ai+ Training platform, many viewable for free when you sign up today.

Originally posted on OpenDataScience.com

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