Online or onsite, instructor-led live Ensemble Learning training courses demonstrate through interactive hands-on practice how to use ensemble machine learning techniques to combine multiple models for improved prediction accuracy and robustness.
Ensemble Learning 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 Ensemble Learning training can be carried out locally on customer premises in Innsbruck or in NobleProg corporate training centers in Innsbruck.
Ensemble Learning is also known as Ensemble Methods or Ensemble Modeling.
NobleProg -- Your Local Training Provider
NobleProg Innsbruck
Valiergasse 58, Innsbruck, Austria, 6020
Overview
Our training facilities are located at Valiergasse 58 in Innsbruck and offer optimal training conditions for your needs.
Directions
The NobleProg training facilities are conveniently located near the main train station, the A12 and A13 motorways are easily accessible.
Parking spaces
There are parking spaces in the surrounding streets around our training rooms.
Local infrastructure
There are numerous restaurants in the downtown area and hotels are also within walking distance.
This instructor-led, live training in Innsbruck (online or onsite) is aimed at beginner to intermediate-level developers and data scientists who wish to learn the basics of LightGBM and explore advanced techniques.
By the end of this training, participants will be able to:
Install and configure LightGBM.
Understand the theory behind gradient boosting and decision tree algorithms
Use LightGBM for basic and advanced machine learning tasks.
Implement advanced techniques such as feature engineering, hyperparameter tuning, and model interpretation.
Integrate LightGBM with other machine learning frameworks.
This instructor-led, live training in Innsbruck (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.
This instructor-led, live training in Innsbruck (online or onsite) is aimed at data scientists and software engineers who wish to use Random Forest to build machine learning algorithms for large datasets.
By the end of this training, participants will be able to:
Set up the necessary development environment to start building machine learning models with Random forest.
Understand the advantages of Random Forest and how to implement it to resolve classification and regression problems.
Learn how to handle large datasets and interpret multiple decision trees in Random Forest.
Evaluate and optimize machine learning model performance by tuning the hyperparameters.
Online Ensemble Methods training in Innsbruck, Ensemble Modeling training courses in Innsbruck, Weekend Ensemble Methods courses in Innsbruck, Evening Ensemble Methods training in Innsbruck, Ensemble Methods instructor-led in Innsbruck, Ensemble Methods private courses in Innsbruck, Ensemble Methods instructor-led in Innsbruck, Ensemble Methods classes in Innsbruck, Ensemble Learning one on one training in Innsbruck, Ensemble Modeling on-site in Innsbruck, Ensemble Learning coaching in Innsbruck, Weekend Ensemble Learning training in Innsbruck, Ensemble Modeling instructor in Innsbruck, Ensemble Methods trainer in Innsbruck, Online Ensemble Learning training in Innsbruck, Evening Ensemble Modeling courses in Innsbruck, Ensemble Modeling boot camp in Innsbruck
