Szczecin

Biuro Aloha, Jerzego Janosika 17, Szczecin, Poland, 71-424

The training room is fully equipped, providing all necessary amenities for participants. Additionally, it has attractive transportation connections to all strategic points of the city, facilitating access for both residents and visitors. It is located just 3 kilometers from the city center, allowing for quick access to other important urban locations and amenities.

Koszalin

Gwardia, Sportowa 34, Koszalin, Poland, 75-503

The training room is equipped with full modern amenities. It is located 3 kilometers from the city center. The facility features ample parking space for training participants, ensuring convenient access for all attendees.

Subcategories (2)

Random Forest

Random Forest
AdaBoost

AdaBoost

Explore Our Courses

LightGBM for Machine Learning

 21 Hours
This instructor-led, live training in zachodniopomorskie (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.
  • Troubleshoot common issues in LightGBM.
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AdaBoost Python for Machine Learning

 14 Hours
This instructor-led, live training in zachodniopomorskie (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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Machine Learning with Random Forest

 14 Hours
This instructor-led, live training in zachodniopomorskie (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.
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