Karma of Humans is AI
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Updated
Mar 9, 2020 - Jupyter Notebook
Karma of Humans is AI
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.
This repository contains introductory notebooks for random forest.
This repository contains introductory notebooks for KNN algorithm
This repository contains introductory notebooks for support vector machine
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.
This repository was made with the intention to practice Machine Learning concepts using Jupyter Notebook.
This is the Data Mining Porject for predicting the grade of student before the final examination and before the Mid 2 examination. I use Python and Jupyter Notebook for this Project.
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.
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