"Supervised" Machine Learning

Workshop Overview

The foundation of AI solutions for decision-making, "Supervised" ML models, are now more accessible to practitioners due to rapid technological advancements. Mastering the most critical predictive models has become more accessible, especially with the improvement of automation tools. This workshop provides a comprehensive overview of "supervised" Machine Learning algorithms and their role in improving predictions across various industries. To ensure practical application, it also explores models using different technologies (SAS, Alteryx, STATISTICA, PYTHON, etc.), enabling participants to become professional practitioners and expert consultants by evaluating and selecting the most suitable solution with the right technical package.

Learning Outcomes

• Explore the rise of AI with IoT and technology capacities.
• Understand the true meaning of Machine Learning (ML).
• Connect Data Analysis to Machine Learning.
• Make it all with f(X) = y.
• Differentiate between Regression and Classification models.
• Validate models with p-value and Accuracy metrics.
• Improve predictions by testing different ML models.
• Fine-tune models with the stepwise methods.
• Compare models using accuracy measures.
• Understand the utility of all cross-validation techniques.
• Design dashboards for comparative models.
• Overview Ensemble Models.

Duration 5 days

Day 1:

- Introduction to Machine Learning

- Multiple Linear Regression

Day 2:

- Simple & Multiple Logistic Regression

- Models Evaluation Indicators

Day 3:

-  Linear and Quadratic Discriminant Analysis

Day 4:

- Decision Trees / Random Forest Trees

- Naive Bayes

Day 5:

- Support Vector Machines

- K Nearest Neighbors

What will it be about?

- Colored PPT documents / Videos.

- The multiple-way model generation.

- All-in-one predictive model solution.

- Quality model indicators.

- Team Competition for Best Model Finding.  

- Complete case studies from A to Z.

- Proprietary tools for data visualization.

- Methods for selecting the best model.

- ROC charts.

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