Saskatoon-HOME INN & SUITES SASKATOON SOUTH

253 Willis Crescent, 253 Willis Crescent, Saskatoon, Canada, S7T 0V2

You'll be within a 10-minute drive of the University of Saskatchewan and Peter Zakreski Regional Park. This spa hotel is 0.1 mi (0.1 km) from Cielo and 0.4 mi (0.6 km) from Evelyn Edwards Park.

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Scaling Data Pipelines with Spark NLP

 14 Hours

This instructor-led, live training in Saskatoon (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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The good humor, support and skills of the trainer.

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Course - Scaling Data Pipelines with Spark NLP

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Upcoming Courses

Scaling Data Pipelines with Spark NLP

2025-07-09 09:30
14 hours
Saskatoon-HOME INN & SUITES SASKATOON SOUTH
CA$ 3,514 (Online)
CA$ 4,514 (Classroom)

Scaling Data Pipelines with Spark NLP

2025-07-23 09:30
14 hours
Saskatoon-HOME INN & SUITES SASKATOON SOUTH
CA$ 3,514 (Online)
CA$ 4,514 (Classroom)

Scaling Data Pipelines with Spark NLP

2025-08-06 09:30
14 hours
Saskatoon-HOME INN & SUITES SASKATOON SOUTH
CA$ 3,514 (Online)
CA$ 4,514 (Classroom)

Scaling Data Pipelines with Spark NLP

2025-08-20 09:30
14 hours
Saskatoon-HOME INN & SUITES SASKATOON SOUTH
CA$ 3,514 (Online)
CA$ 4,514 (Classroom)

Scaling Data Pipelines with Spark NLP

2025-09-03 09:30
14 hours
Saskatoon-HOME INN & SUITES SASKATOON SOUTH
CA$ 3,514 (Online)
CA$ 4,514 (Classroom)

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Spark NLP Consulting
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