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Course Outline
Introduction
Overview of DataRobot Features and Architecture
Setting up a DataRobot Account
Preparing and Loading Data
Analyzing Datasets
Modeling with DataRobot
Beginning the Modeling Process
Streamlining Model Development With DataRobot
Evaluating Results of Automated Modeling
Interpreting Models and Text Features
Generating Model Documentation
Making Predictions from Datasets
Deploying Models Built in DataRobot
Monitoring and Managing Deployed Models
Integrating DataRobot in Production
Managing DataRobot Projects
Summary and Conclusion
Requirements
- Experience with data analytics
- Familiarity with machine learning
Audience
- Data scientists
- Data analysts
Testimonials
He was very informative and helpful.
Pratheep Ravy
the scope of material
Maciej Jonczyk
systematizing knowledge in the field of ML
Orange Polska
Richard's training style kept it interesting, the real world examples used helped to drive the concepts home.
Jamie Martin-Royle - NBrown Group
The content, as I found it very interesting and think it would help me in my final year at University.
Krishan Mistry - NBrown Group
the matter was well presented and in an orderly manner.
Marylin Houle - Ivanhoe Cambridge
The remote classroom setting worked very well
- Trimac Management Services LP
Good detail on what R is used for and how to start using it right away
Hoss Shenassa - Trimac Management Services LP
The many practical examples / assignments that we went through were great. For me, I learn better by seeing examples and applying them elsewhere. The use of real data and applying what was taught against it was extremely valuable. Michaels PowerPoint presentations and his ability to work through each solution was invaluable.
- Trimac Management Services LP
The exercises.
Elena Velkova - CEED Bulgaria
Practical exercises with R were very helpful.
CEED Bulgaria
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