Learning to create Machine Learning Algorithms

Implementation of basic ML algorithms from scratch in python...

ApnaAnaaj aims to solve crop value prediction problem in an efficient way to ensure the guaranteed benefits to the poor farmers. The team decided to use Machine Learning techniques on various data to came out with better solution. This solution uses Decision Tree Regression technique to predict the crop value using the data trained from authenti…

This repository will contain all the stuffs required for beginners in ML and DL do follow and star this repo for regular updates

In this project we are comparing various regression models to find which model works better for predicting the AQI (Air Quality Index).

Machine Learning Software that predicts planets based on their distance from the sun, number of satellites and various properties

Compared different classification and regreesion models performance in scikit-learn by applying them on 20 datasets from UCL website.

Introduction to XGBoost with an Implementation in an iOS Application

The objective of this project is to study the COVID-19 outbreak using basic statistical techniques and make short term predictions using ML regression methods.

Implements Decision tree classification and regression algorithm from scratch in Python.

Natural Gas Price Prediction System Using IBM Watson services

This is repository about the MachineLaering Basics including all the Machine learning Algorithms

Machine Learning algorithms implementation using Python

Implementation of a 1D Decision Tree Regression model in python.

Weather Prediction iOS Application Using Flask API and AI

Academic project for Advances in Data Science and Architecture course

Segmentación Energía usando dataset REDD y varios algoritmos incluidos Neural Network

A ReactJS based dashboard predicting crop prices using Decision Tree Regression Algorithm.

Los árboles de decisión son uno de los algoritmos clásicos de machine learning ya que nos ayudan a visualizar las predicciones hechas por nuestro modelo. En este tutorial vemos su uso para regresiones lineares y clasificación, así como herramientas de ensamble como bagging y boosting.

Implementing a music recommender with decision tree.