Online or onsite, instructor-led live AdaBoost training courses demonstrate through interactive hands-on practice how to use AdaBoost to build boosting algorithms for machine learning with Python.
AdaBoost 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 AdaBoost training can be carried out locally on customer premises in San José or in NobleProg corporate training centers in San José.
AdaBoost is also known as Adaptive Boosting.
NobleProg -- Your Local Training Provider
San Jose - Plaza Roble Las Terrazas
Centro Corporativo Plaza Roble, San José, Costa rica
The San Jose Plaza Roble Las Terrazas Center is situated in one of six buildings connected by covered walkways that make up the secure Plaza Roble complex. With direct access to a major highway intersection, it is easy to get to downtown San Jose, 7km away, and a 15-minute drive to the international airport.
San Jose - Boulevard Dent
6184 Boulevard Dent San Jose San Pedro , San Jose, Costa rica, 11501
Create a fresh headquarters for your company in Costa Rica, featuring fully equipped office facilities at 6184 Boulevard Dent. Dive right into operations in the rapidly expanding capital, situated within the vibrant business hub of The Alameda. Benefit from convenient access to public transportation via bus and train for commuting, as well as the attractions of Downtown San Jose.
This instructor-led, live training in San José (online or onsite) is aimed at data scientists and software engineers who wish to use AdaBoost to build boosting algorithms for machine learning with Python.
By the end of this training, participants will be able to:
Set up the necessary development environment to start building machine learning models with AdaBoost.
Understand the ensemble learning approach and how to implement adaptive boosting.
Learn how to build AdaBoost models to boost machine learning algorithms in Python.
Use hyperparameter tuning to increase the accuracy and performance of AdaBoost models.
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