Classical Machine Learning (ML)

Supervised, Unsupervised, Ensemble and Reinforced Learning Algorithms.


3 to 4 p.m., Feb. 1, 2023
3 to 4 p.m., Feb. 8, 2023
3 to 4 p.m., Feb. 15, 2023
3 to 4 p.m., Feb. 22, 2023
3 to 4 p.m., March 1, 2023
3 to 4 p.m., March 22, 2023
3 to 4 p.m., March 29, 2023
3 to 4 p.m., April 5, 2023
3 to 4 p.m., April 12, 2023
3 to 4 p.m., April 26, 2023

Machine learning is a field that gives computers the ability to learn without being programmed. Machine learning explores the study and construction of algorithms that can learn from and make predictions on data. Such algorithms operate by building a model from an example training set of input data in order to make data-driven predictions.

Currently, the field of Machine Learning development is one of the most active fields supporting scientific research and technological advancements in all domains of knowledge.

This weekly workshop will guide the participants in an on-hands training example in the different Machine Learning algorithms, using libraries and tools from both R and Python programming languages used in real Data Science applications.

   Applications covered in this workshop include:
   - Supervised Learning: Classification and Regression Algorithms
   - Unsupervised Learning: Clustering, Dimension Reduction and Pattern Search Algorithms
   - Ensemble Methods: Bagging and Boosting Algorithms
   - Reinforcement Learning Algorithms

Zoom link for this workshop

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Carlos Lizarraga
Greg Chism