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Hands on Introduction to Apache Spark, ML, SPSS Modeler, Operationalizing Models, and Decision Optimization for Data Engineers, Data Scientist and Developers

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Spark, Machine Learning, Operationalization, Decision Optimization, and Graphical Modeling

POT Hands on Labs

Hands on Introduction to Apache Spark, NLP, ML and Operationalizing Models for Data Engineers, Data Scientist and Developers

POT Summary

IBM is offering a no charge proof of technology for clients and practitioners on Apache Spark, Machine Learning, Operationalization, Decision Optimization, and Graphical Modeling.

This is a half day of education with hands on exercisesinstructed in person by Open Sourceexperts. The POT will provide a detail overview and the exercises will be performed on Jupyter notebooks with publiclyavailable datasets. Participants will use IBM’s flexible data science offering.

Prerequisite:

A basic knowledge of Coding (Preferred Python and/or Scala) and SQL.

Agenda

Expect to spend a half day of lecture and hands on exercises attacking real-world data challenges using Apache Spark, ML, SPSS, DO, and Models. In 4 hours, you will learn the essentials of why these solutions are important to your organization and data science process. This workshop will focus on data wrangling, machine learning, and operationalizing the model.

  • 9:30 pm - 10:00 pm Breakfast/Socialize
  • 10:00 pm - 10:15 pm Kickoff/Introductions/Account Setup
  • 10:15 pm - 11:00 pm Lab 1 Predicting Heart Failure with Python/Spark Machine Learning
  • 11:00 pm - 12:00 pm Lab 2 Predicting Heart Failure with SPSS Model Flows on DSXL
  • 12:00 pm - 12:30 pm Lunch
  • 12:30 pm - 1:15 pm Lab3 Nurse Scheduling with IBM Decision Optimization
  • 1:15 pm - 2:00 pm Use Case Discussion
  • 2:00 pm - 3:00 pm Wrap up & Additional Questions

Data Science Experience POT 1 Assets

Notebooks and assets from DSX POT 1

Data Science Experience POT 1

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Hands on Introduction to Apache Spark, ML, SPSS Modeler, Operationalizing Models, and Decision Optimization for Data Engineers, Data Scientist and Developers

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