When you wish to listen to your favorite song, do you search it yourself or ask Alexa to do it? Many people now prefer the second option. Virtual assistants like Alexa, Cortona are readily embedding in our everyday lives. TechCrunch reports that the global smart speaker sales reached a whopping 146.9 million units in 2019, growing by 70 percent compared to sales in 2018. Amazon’s Echo brand continued to lead the smart speaker sales with a share of 26.2 percent.
While conversing with Alexa seems to be very convenient, there is a complex algorithm working behind it that most of the people do not care to know about. That technique is known as Natural Language Processing (NLP). It is an important form of Artificial Intelligence (AI) and has been in action for quite some time now.
This article lets you know more about NLP, top reasons to learn NLP, and why you should take a natural language processing course.
Natural Language Processing, simply put, refers to an automated way by which machines interpret and analyze natural human languages through algorithms to extract information. It has revolutionized the interaction between humans and machines. NLP takes many forms when used, but at the core, it assists machines in understanding and communicating with human speech. NLP isn’t a new science, but it has only recently become viable.
A massive amount of text data is being generated every day. From medical records to social media, the generated data is mostly unstructured. Automation is needed to analyze such text and speech data efficiently. It is NLP that extracts content from unstructured data, finds subtle patterns in disparate data sets, and thus enables machine-to-human communication. It is generally used in text and social media analytics tools to analyze opinions and issues.
Top Reasons to Learn NLP
If you are looking for a career in AI, then the knowledge of NLP would surely be beneficial. Here are some of the top reasons why professionals prefer to learn NLP.
NLP has various applications
Virtual assistants are just one of the popular applications of NLP. Sentiment analysis, text classification, chatbots, customer experience, speech to text conversion and vice versa, are some of the other areas where NLP has been leveraged. The common goal behind all these applications is to take raw language input and use algorithms and linguistics to transform the text to gain meaningful insights. Sectors like banking, insurance, healthcare, retail, media find NLP useful for fraud detection, risk and compliance management, asset management, predictive maintenance, and even client service.
NLP is a major contributor to the growing AI market
The global artificial intelligence software market would witness massive growth, with revenues expected to reach $118.6 billion by 2025 from around $9.5 billion in 2018. Applications like NLP along with Robotic Process Automation (RPA) and Machine Learning largely form the overall AI market. NLP is driving many forms of AI that humans are seeing today. Many enterprises are now exploring their ways to use this technology to develop the most favorable applications.
Demand is high
No company today wants to ignore digital transformation. Every business is trying to leverage the power of AI, be it for marketing campaigns, banking services, or to give users a personalized experience. Text data forms a large portion of the unstructured data that companies are analyzing to identify patterns and make data-driven decisions. As such, professionals skilled in NLP will be in high demand for projects involving text analytics.
NLP is here to stay
Though not hyped as much as Big Data or Machine Learning, NLP is already helping humans with their day-to-day tasks. Growing smartphone functionalities, usage of smart devices, and automation of more routine human activities through Big Data would drive the adoption of NLP in the future. When combined with IoT applications, NLP would facilitate humans to control smart appliances through voice. Companies would use it to manage data more effectively, provide enhanced customer experience, and more.
Clearly, it is beneficial for professionals to learn NLP and enhance their AI career. Does this mean you need to go back to university and earn a degree in NLP? Definitely not! Thanks to NLP online training programs which give learners comprehensive knowledge of NLP concepts. We encourage you to do a bit of research and enroll in a course offered by a trusted eLearning platform. Make sure that the course covers important topics of NLP like statistical machine translation and neural models, neural knowledge base embedding, deep semantic similarity model (DSSM), neural models applied in image captioning, deep reinforcement learning technique, and visual question answering using Python’s Natural Language Toolkit (NLTK). Taking this one step can be the most appropriate decision for your career.