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Featured Class at LiveWorx: "Applying Machine Learning using ThingWorx Analytics"


Featured Class at LiveWorx: "Applying Machine Learning using ThingWorx Analytics"

As we are getting into the "hot" phase of final preparations for LiveWorx, we are seeing more and more questions from attendees on individual classes offered. People are finalizing their agendas and training sessions.


There are only a few slots available for some of the full day classes we are running on the days before and after the conference. These full-day classes are very popular, as they are small-sized deep dives into a given topic and they are sold with a 50% discount off the regular training day rate.


We had an inquiry for the ThingWorx Analytics class just this week and the customer requested more information on the content. As we currently have 3 more seats left, we thought we'd share this information here to help others with their registration planning.


Course Structure: "Applying Machine Learning using ThingWorx Analytics"

(The following lists the modules of the course and a brief explanation of what will be covered in that module.)


  1. ThingWorx Analytics Overview: Here we will introduce what machine learning is and how, at a high level, our solution implements this and the use cases our solution is capable of handling
  2. Application Program Interface (APIs): Here we will train you on what a RESTful API is and how to interact with it so that you can interact and make use of ThingWorx Analytics
  3. Data Profiling: Here you will learn some of the basic elements of usable machine learning data such as data quality, data types, and usability.
  4. Data Transformation and Feature Engineering: Here you will learn some basic aspects of features and feature engineering in support of applied machine learning.
  5. Descriptive Analytics: Here you will learn jobs that can be run in ThingWorx Analytics that provides descriptive algorithm outputs and how to interpret them.
  6. Predictive Models and Model Validation: Here you will learn how to build your own predictive model and assess the validation of such a model against test data.
  7. Scoring: Here is where you will take a model that has been developed and score individual records to see what the prediction is given the parameters of the model.
  8. Machine Learning and ThingWorx Integration: We will introduce some high level concepts behind how to integrate machine learning into ThingWorx.


If you would like to register for this class on June 6, please go to the registration tool on LiveWorx 2016 | The Premier IoT Business Event | Take a Fresh Look at Things and add it to your event registration.


Of course, we will be happy to answer any further questions, too!


See you in Boston!



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