TX, Houston - Downtown - Pennzoil Plaza

700 Milam Suite 1300, Houston, United States, 77002

The venue is located just next door to the Jones Hall for the Performing Arts with the entrance just across the street from the Bank of America Center.

TX, Dallas - Downtown Republic Center

Downtown Republic Center, 325 N. St. Paul Street Suite 3100, Dallas, United States, 75201

The venue is located in the iconic Republic Tower, conveniently situated in the heart of downtown Dallas, on the crossing of North Saint Paul Street and Bryan Street and just down the road from the St Paul Station.

TX, Austin - Littlefield Congress

106 E 6th St Suite 900, Austin, united states, 78701

The venue is located in the Littlefield Bvilding between the Capital One Cafe and the Due Forni Pizza and Wine.

Subcategories (2)

Category for Random Forest

Random Forest
Category for AdaBoost

AdaBoost

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LightGBM for Machine Learning

 21 Hours

This instructor-led, live training in Texas (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 Texas (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 Texas (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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