Online or onsite, instructor-led live Spark NLP training courses demonstrate through interactive hands-on practice how to use Spark NLP, built on top of Apache Spark, to develop, implement, and scale natural language text processing models and pipelines.
Spark NLP training is available as "online live training" or "onsite live training". Online live training (aka "remote live training") is carried out by way of an interactive, remote desktop. Onsite live Spark NLP training can be carried out locally on customer premises in Lima or in NobleProg corporate training centers in Lima.
NobleProg -- Your Local Training Provider
Lima - Edificio Tempus San Isidro
Av. Santo Toribio 115, Lima, Peru, 27
Edificio Tempus is a Class A brand new office building is strategically located in the corner of Av Victor Belaunde and Av. San Toribio in the heart of San Isidro. There is plenty of parking on 4 parking decks. This center is only a short 300 mt walk in the same block from our exiting Real Seis in located in Centro Empresarial.
Lima - Miguel Grau
Av. Almte. Miguel Grau 709 Lima , Lima, Peru, 15063
Expand your business horizons with a workspace in Barranco, one of Lima's 43 districts, boasting excellent connectivity to its surroundings. Enjoy effortless commuting to your office via the Avenida Almirante Miguel Grau S/N and Bulevar - Embarque Sur 2 bus stops.
This instructor-led, live training in Lima (online or onsite) is aimed at data scientists and developers who wish to use Spark NLP, built on top of Apache Spark, to develop, implement, and scale natural language text processing models and pipelines.
By the end of this training, participants will be able to:
Set up the necessary development environment to start building NLP pipelines with Spark NLP.
Understand the features, architecture, and benefits of using Spark NLP.
Use the pre-trained models available in Spark NLP to implement text processing.
Learn how to build, train, and scale Spark NLP models for production-grade projects.
Apply classification, inference, and sentiment analysis on real-world use cases (clinical data, customer behavior insights, etc.).
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