Introduction NumPy (short for Numerical Python) is a powerful Python library for numerical computing. It provides support for large, multi-dimensional arrays and matrices, as well as a wide range of mathematical functions to operate on these arrays. NumPy is widely used in scientific computing, data analysis, and machine learning applications. Read more…
Pandas is a popular open-source library used for data manipulation and analysis in Python. It is built on top of NumPy, another popular library for numerical computations in Python which we will cover in the future. Pandas provides data structures and functions for efficient and easy handling of large and Read more…
Matplotlib is a popular Python library used for data visualization. It provides a wide range of plotting functions that allow you to create various types of 2D and 3D plots. In this blog post, we’ll go over the basics of using Matplotlib for beginners, including code examples for the most Read more…
El control de versiones es una herramienta esencial para el desarrollo de software que permite a los desarrolladores realizar un seguimiento de los cambios en su código y colaborar eficazmente con otros miembros del equipo. Git es uno de los sistemas de control de versiones más populares, utilizado por desarrolladores Read more…
Version control is an essential tool for software development that enables developers to keep track of changes to their codebase and collaborate effectively with other team members. Git is one of the most popular version control systems, widely used by developers worldwide. Git works by creating a history of changes Read more…
Los Jupyter Notebooks son una herramienta muy poderosa cuando trabajas con Python. Te permite iterar más rápido sobre los cambios de tu código, ejecutando ciertas secciones del código sin tener que ejecutarlo todo de nuevo. Nosotros lo usamos para nuestro artículo Implementación Básica de K-Means, esto nos permite ver el Read more…
Jupyter Notebooks are a very powerful tool to know when you are working with Python. It allows you to iterate faster over code changes, executing specific sections of the code without the need of running it all. As an example, we used it for our Basic K-Means implementation post, where Read more…
Setup En un artículo anterior, explicamos el algoritmo de K-Means. Para llegar a entenderlo mejor, lo vamos a implementar en Python desde cero. Para instalar todas las herramientas necesarias puedes seguir nuestros artículos de setup para Windows o para Linux. Para mejorar la presentación de este artículo, sólo vamos a Read more…
Setup In a previous post, we talked about the K-Means algorithm. In order to better understand how this algorithm works we will implement it from scratch in Python. To install the necessary tools please make sure to follow our setup posts either for Windows or for Linux. To improve the Read more…
To start working on Machine Learning you need tools, and those tools need to be installed in an environment. Think of an environment as a kind of workshop, except instead of a hammer or a screwdriver, you have Python and Keras. We will go through how to set up a Read more…