Machine Learning with R, the tidyverse, and mlr samenvattingen

The main objective is to write a fully executed R-Markdown program performing dimension reduction on a high dimensional image data using MNIST (digits) and Fashion MNIST (apparel) images that are 28 x 28 pixels resolution. Make sure to describe the final hyperparameter settings of all algorithms that were used for comparison purposes.

Write a formal report on your findings from the last several weeks for the regression problem of the Nutrition Case Study. The main objective is to write a fully executed R-Markdown program performing regression prediction using the best models found for and comparing the cost functions and R-square values. Make sure to describe the final hyperparameter settings of all algorithms that were used for comparison purposes. Perform EDA on MNIST and Fashion MNIST data and share your findings in the...

The objective is to write a formal analysis report finishing the objectives set forth in the final case analysis document. A sample template for the final report is provided that contains minimum requirements for the report including the following sections: Introduction, Analysis and Results, Methodology, Limitations and Conclusion. You are required to follow the report template and explain the findings including final models ran for the task.

Write a fully executed R-Markdown program and submit a pdf / word or html file. The program should merge / join the data files given to you as part of the Santander Bank Case Study. You are then required to perform Exploratory Data Analysis (EDA) along with describing the features of the response variable, visualizing a few predictors, and clearly explaining the findings.

Perform SVM on the ranking task from previous week.

Santander Bank Case Study Write a formal report on your findings from the last several weeks for the classification of the Santander Bank Case Study. The main objective is to write a fully executed R-Markdown program performing classification using the best models found for logistic regression, SVM, Random Forest and XGBoost algorithms, and comparing the values of their cost functions and accuracy scores.

You are expected to be able to program in R prior to taking this class. Use the titanic dataset from CRAN and perform EDA on various columns. Without using any modeling algorithms, and only using basic methods such as frequency distribution, describe the most important predictors of survival of Titanic passengers, e.g. were males or females more likely to survive, were young and rich females more likely to survive than old poor males etc?