Auto-Keras Training in Michigan

Auto-Keras Training in Michigan

Online or onsite, instructor-led live Auto-Keras training courses demonstrate through interactive hands-on practice how to use Auto-Keras to automate the process of selecting and optimizing a machine learning model.

Auto-Keras training is available as "online live training" or "onsite live training". Online live training (aka "remote live training") is carried out by way of an interactive, remote desktop. Onsite live Auto-Keras training can be carried out locally on customer premises in Michigan or in NobleProg corporate training centers in Michigan.

Auto-Keras is also known as Autokeras or Auto Keras.

NobleProg -- Your Local Training Provider

MI, Detroit - Renaissance Center

MI, Detroit - Renaissance Center
400 Renaissance Center Suite 2600
Detroit, MI 48243
United States
,
See map: Google Maps
Michigan US
 MI, Detroit - Renaissance Center
Learn Auto-Keras in our training center in Michigan. The venue is located in the Renaissance Center, the same location as General Motors and the Mariott Hotel. Read more

MI, Ann Arbor – South State Commons

Ann Arbor
2723 South State Street Suite 150
Ann Arbor, MI 48104
United States
,
See map: Google Maps
Michigan US
MI, Ann Arbor – South State Commons
Learn Auto-Keras in our training center in Michigan. The venue is located in the same building as Wells Fargo Advisors and Dykema, in the vicinity of Germain Honda of Ann Arbor and Plante Moran. Read more

Autokeras Course Events - Michigan

Auto Keras Course Outlines in Michigan

Course Name
Duration
Overview
Course Name
Duration
Overview
14 hours
This instructor-led, live training in Michigan (online or onsite) is aimed at data scientists as well as less technical persons who wish to use Auto-Keras to automate the process of selecting and optimizing a machine learning model.

By the end of this training, participants will be able to:

- Automate the process of training highly efficient machine learning models.
- Automatically search for the best parameters for deep learning models.
- Build highly accurate machine learning models.
- Use the power of machine learning to solve real-world business problems.

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