IBM Watson Natural Language Understanding (NLU) is a cloud-based service that uses machine learning to analyze and extract metadata from text. It performs tasks such as sentiment analysis, entity recognition, keyword extraction, and concept tagging to help understand the context and meaning of the text.

About IBM Watson NLU
IBM Watson NLU was developed by IBM as part of its Watson suite of AI services. It evolved from earlier natural language processing technologies and was officially launched in 2016. The service was created to leverage machine learning for analyzing and understanding unstructured text data, aiming to help businesses extract valuable insights from large volumes of textual information.
Strengths of IBM Watson NLU include robust text analysis capabilities, high accuracy in sentiment and entity recognition, and seamless integration with other IBM services. Weaknesses include higher costs compared to some alternatives and potential complexity in setup and customization. Competitors include Google Cloud Natural Language API, Microsoft Azure Text Analytics, and Amazon Comprehend.
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How to hire a IBM Watson NLU expert
An IBM Watson NLU expert must have skills in natural language processing (NLP), machine learning, and data analysis. They should be proficient in programming languages such as Python or JavaScript, familiar with RESTful APIs, and experienced in integrating Watson NLU with other systems. Knowledge of JSON and XML for data interchange is also essential.

Tamiris G.
Skills
Possessing extensive experience in software engineering, this candidate expertly navigates the software development lifecycle from ideation to deployment and excels in various domains, including API development, Computer Vision, Natural Language Processing (NLP), and AI/ML applications. With a pronounced focus on Data Science, expertise in Python programming, and hands-on experience in utilizing AI/ML techniques on unstructured data types such as video, audio, and text, they are poised to drive impactful data-driven solutions. Their professional journey includes leading the development of applications for data extraction, video analytics, and the implementation of efficient database systems. Committed to generating value through data insights, they demonstrate a strong capacity for collaborating across technical and business teams to deliver refined and functional software solutions.

Matheus D.
Skills
An accomplished Machine Learning Engineer with over four years of experience in technology and three years in research, holding a Master's degree in Data Science and AI supported by the prestigious Eiffel Excellence Scholarship. Demonstrates international adaptability with professional experiences in Brazil, France, and Japan, collaborating with diverse teams across more than ten countries. Proven expertise in enhancing deep learning models, implementing natural language processing solutions, and developing robust data pipelines, with a strong proficiency in utilizing tools such as PyTorch, Azure, and Docker. Actively seeking opportunities as a Machine Learning Engineer, Data Scientist, or Data Engineer, with an openness to industrial PhDs.
*Estimations are based on information from Glassdoor, salary.com and live Howdy data.
USA
$ 224K
Employer Cost
$ 127K
Employer Cost
$ 97K
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