This repository was made with the intention to practice Machine Learning concepts using Jupyter Notebook.

📈📊 Data Science Notebooks . ▫️ Aplicación de algoritmos de ML para la resolución de problemas de aprendizaje supervisado (Clasificación y Regresión)

This notebook demonstrates how to do cross-validation (CV) with linear regression as an example (it is heavily used in almost all modelling techniques such as decision trees, SVM etc.). We will mainly use sklearn to do cross-validation.

This notebook tested the performance of the following scikit-learn models: Logistic Regression, Multilayer Perception, Naive Bayes, KNN, and Random Forest Classifier in classifying whether a person has thyroid or not based on the dataset provided. Each model’s performance has been evaluated using the F1 Score. NOTE: This notebook was used for a …

Aquí compartiré y documentaré mi aprendizaje en el análisis predictivo utilizando ML y prácticas de Python. Variando desde simples ejercicios hasta proyectos prácticos. Cada proyecto incluye archivos de soporte y notebooks con código y análisis y las prácticas sus enunciados comentado al inicio.

This repository contains introductory notebooks for KNN algorithm

This repository contains introductory notebooks for random forest.

This repository contains introductory notebooks for support vector machine

This project aims to predict house prices using a machine learning model. The project involves data cleaning, feature engineering, model selection, training, and evaluation. The dataset is uploaded by the user, and the model is trained to predict house prices based on various features.

This repository consists the Jupyter Notebook files containing code of Artificial Neural Network with different tuning parameters for a similar scenario.

The following Google Colaboratory notebooks create a classifier model to be able to predict whether a machine will fail in the next 12 hours.

A notebook aimed at predicting and improving water safety by analyzing contaminants and pollution levels in water sources, enhancing public health and ensuring access to clean drinking water.

This is the Data Mining Project for predicting the student's grade before the final and Mid-2 examination. I use Python and Jupyter Notebook for this Project.

A notebook about commonly used machine learning algorithms.

This project involves the prediction of house prices in Boston using Lasso Regression in Jupyter Notebook. The dataset contains features such as average number of rooms per dwelling, crime rate, and more. Through this analysis, we aim to build a regression model that accurately predicts house prices based on the given input features.

Karma of Humans is AI