Google AutoML Natural Language is a machine learning tool that enables users to build custom natural language processing models. It automates the process of training, evaluating, and deploying these models for tasks such as sentiment analysis, entity recognition, and text classification.

About Google AutoML Natural Language
Google AutoML Natural Language was launched by Google in 2018. It was developed to simplify the creation of custom natural language processing models, making advanced machine learning accessible to users without extensive expertise in the field.
Strengths of Google AutoML Natural Language include ease of use, automated model training, and integration with Google's ecosystem. Weaknesses include potential high costs and limited customization options for advanced users. Competitors include Amazon Comprehend, Microsoft Azure Text Analytics, and IBM Watson Natural Language Understanding.
Hire Google AutoML Natural Language Experts
Work with Howdy to gain access to the top 1% of LatAM Talent.
Share your Needs
Talk requirements with a Howdy Expert.
Choose Talent
We'll provide a list of the best candidates.
Recruit Risk Free
No hidden fees, no upfront costs, start working within 24 hrs.
How to hire a Google AutoML Natural Language expert
A Google AutoML Natural Language expert must have skills in data preprocessing, model evaluation, and deployment. Proficiency in using Google Cloud Platform, understanding of natural language processing concepts, and experience with machine learning workflows are 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
Benefits + Taxes + Fees
Salary
The Best of the Best Optimized for Your Budget
Thanks to our Cost Calculator, you can estimate how much you're saving when hiring top LatAm talent with no middlemen or hidden fees.