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 Ohio or in NobleProg corporate training centers in Ohio.
Auto-Keras is also known as Autokeras or Auto Keras.
NobleProg -- Your Local Training Provider
230 W. Huron Road, Cleveland, OH, united states, 44113
Learn Auto-Keras in our training center in Ohio. Cincinnati, OH - The venue is located just across the street from the Taft Theatre and just behind the First Financial Center
Auto-Keras Course Events - Ohio
AutoML with Auto-Keras - OH, Cleveland - Cleveland City Center
2023-10-07 09:30
OH, Cleveland - Cleveland City Center
14 hours
AutoML with Auto-Keras - OH, Cleveland - Cleveland City Center
2023-10-21 09:30
OH, Cleveland - Cleveland City Center
14 hours
AutoML with Auto-Keras - OH, Cleveland - Cleveland City Center
2023-11-04 09:30
OH, Cleveland - Cleveland City Center
14 hours
AutoML with Auto-Keras - OH, Cleveland - Cleveland City Center
2023-11-18 09:30
OH, Cleveland - Cleveland City Center
14 hours
AutoML with Auto-Keras - OH, Cleveland - Cleveland City Center
2023-12-02 09:30
OH, Cleveland - Cleveland City Center
14 hours
AutoML with Auto-Keras - OH, Cleveland - Cleveland City Center
2023-12-16 09:30
OH, Cleveland - Cleveland City Center
14 hours
AutoML with Auto-Keras - OH, Cleveland - Cleveland City Center
This instructor-led, live training in Ohio (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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