Probability and Machine Learning
Probability allows us to model uncertainty and make informed decisions. In this article, we will explore how this tool is used in the context of machine learning.
Statistics and Machine Learning
Statistics allows us to analyze and understand data. In this article, we will explore more about descriptive and inferential statistics, and how these concepts are fundamental for machine learning.
Vectors and Machine Learning
Vectors are a fundamental part of machine learning, as they allow for the efficient representation of data and model parameters. In this article, we will explore their definition and application in machine learning algorithms.
Experimenting with the Titanic Survival Dataset
Let's explore the Titanic survival dataset using exploratory data analysis (EDA) techniques to discover patterns and relationships between passenger characteristics and their survival.
Experimenting with Exploratory Data Analysis
In this article, we will explore the process of exploratory data analysis (EDA) in the context of machine learning projects.
The workflow in Machine Learning projects
Discover the typical workflow of a machine learning project, from data collection to model implementation, and learn about best practices and common challenges in the field of data science.
Machine learning paradigms and mathematical foundations
Types of machine learning, common algorithms and essential mathematical foundations for understanding how machine learning models work.
Machine Learning Fundamentals
Basic concepts for starting in the world of machine learning
Getting Started with Vue 3 and Vite
A complete guide to configure your first Vue 3 project with Vite, including best practices and modern tools.
