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Introduction

What is this repository about?

• In this repository, the progress carried out to completing the tasks of the course Machine Learning (ESI, Ciudad Real) will be uploaded. In this way, the project advancements will be updated and documented consistently.
• For each progress task, a different wiki section is specified in order to document everything correctly.

General goals

• Apply Machine Learning theory to practical Problems.
• Develop proficiency in ML algorithms and techniques.
• Maintain collaboration and common work while learning together.

Progress Tasks

Progress Task 1:

• In this first practice, we have to use a dataset of wine characteristics to predict the quality of wine by comparing the performance of regression and classification algorithms. Therefore, the procedure is:

      1. Select and implement a classification and a regression algorithm to test.
      2. Analyze their performance.
      3. Draw conclusions based on the results.
      4. Compare both models' performance.
      5. Conclude which approach (regression vs. classification) is more suitable for this problem and why.
  
      - It is essential to justify the choice of each algorithm, the metrics selected and their interpretations.
  

• To access more information about the Wine Quality dataset, click here.

Progress Task 2:

• Not started yet.

Progress Task 3:

• Not started yet.