Machine Learning: Supervised Learning

The goal of this post is to present the most popular supervised learning algorithms.

There are two types supervised learning algorithms: regression and classification. Both of them have the goal to make a prediction based on input data provided during the training. In that input data we have information about the independent variables and dependent variables. The dependent variable is what the algorithm will predict later using new data.

Regression: The dependent variable is a number.

  • Linear Regression
  • Polynomial Regression
  • Support Vector Regression (SVR)
  • K-nearest neighbors (KNN)
  • Decision Trees & Random Forest

Classification: The dependent variable is a category.

  • Logistic Regression (Binary classification)
  • Naive Bayes
  • Support Vector Machine (SVM)
  • K-nearest neighbors (KNN)
  • Decision Trees & Random Forest

Supervised Learning

Big resolution image.

What I did the last 3 years

I had no time to write something for a while, the goal of this post is to summarize what did last years beside my job.

1. Master’s degree: Data Analytics and Business Intelligence

I decided to come back to the university to study Data Science I completed the following studies:

Master’s degree Business Intelligence 2018 – 2019 (Universitat Oberta de Catalunya – Spain)
– Gather and analyze information relevant to a company’s environment.
– Business oriented data analytics. (Customer and operations analytics)
– Use of procedures, skills, applications, tools and practices to support decision-making.

Post degree Data Analytics and Big Data 2016 – 2018 (Universitat Oberta de Catalunya – Spain)
– Data mining, data analytics and visual analytics.
– Data management, data governance and Big Data.
– Machine learning and artificial intelligence.

During that time I was involved in a couple of personal projects beside my job in OMICRON Electroncis.

2. Data Analyst hobbyist

I supported the eSport club x6tence doing data analysis for Clash Royale. To do this a webpage and a database SQLServer in Azure was used to do the data acquisition and PowerBI to do the Data Analysis.

This project was excelent to apply a lot of things that I was learning during my studies, special mention to PowerBI.

3. Software Development: Doctor Decks

Doctor Decks was a project in which I work together with a work colleague. The goal of the software was to find good combinations of cards for the game Clash Royale. The product was available in a web and also had phone apps: Windows universal, iOS and Android. A cloud app in Microsoft Azure was collecting the data from differents apis.

This was an excelent project to learn a lot about data analysis and improve my knowledge about Azure Cloud, web development with Angular and apps development with Xamarin.

The web had thousands of visits everyday and the app more than 1M downloads! After more than two years of success we decided to finish the project due to the maintenance effort.