Data Science course in R

On October 20, I will teach a Data Science course using R.

The topics covered will be:

• Data Cleaning
• Supervised classification models:
  • Logistic regression.
  • Naive Bayes.
  • Trees and Random Forest.
  • Neural Networks.
  • Grid Search (hyperparameter tuning).
  • Evaluation of classification models.
• Unsupervised models:
  • Dimensionality Reduction (PCA) -> Applied example of replicating an investment fund with PCA.
  • Segmentation: K-Means.
  • Association Rules.
• Web applications in R:
  • Shiny

You can buy tickets at: https://welcu.com/metric-learning/intensivo-de-r-para-data-science

If you have any questions, you can email me at danielfm123@gmail.com or marco@metricars.com