AR, Little Rock - Regions Center

10800 Financial Centre Pkway #125, Little Rock, united states, 72211

Experience a professional, modern workspace at the Regions Center office at 400 West Capitol Avenue in the heart of d...

AZ, Phoenix - Central Ave Suite 1400

40 North Central Ave, Suite 1400, Pheonix, united states, 85004
The center is conveniently located in downtown Phoenix and in just walking distance to numerous restaurants, shops, and busin...

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Scaling Data Pipelines with Spark NLP

14 Hours
This instructor-led, live training in Arizona (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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Testimonials (5)

Exercises and exchanges during questions/answers

Antoine - Physiobotic
Course - Scaling Data Pipelines with Spark NLP

Machine Translated

The good humor, support and skills of the trainer.

Oumayma - Physiobotic
Course - Scaling Data Pipelines with Spark NLP

Machine Translated

This is one of the best hands-on with exercises programming courses I have ever taken.

Laura Kahn
Course - Artificial Intelligence - the most applied stuff - Data Analysis + Distributed AI + NLP

I did like the exercises.

Office for National Statistics
Course - Natural Language Processing with Python

Los ejemplos y la paciencia del instructor

José Emilio Sánchez García - Universidad Autónoma Indígena de México
Course - Natural Language Processing with TensorFlow

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