This repository contains my final project for UT Austin's Data Analytics Bootcamp. My teammates and I explored a Wine Reviews dataset and built an interactive Tableau dashboard to recommend wines for a novice based on price, rating, variety and country. We also built a machine learning model to train it to rate wine like an experienced sommelier.

Build a Machine Learning model to identify the habitability score of the property based on the property's basic information and location-based information.

Regression techniques

In this project, I have used Random forest Regressor and done a lot of data preprocessing on raw data finally get an accuracy of approximately 81 percent. This project mainly focuses on data preprocessing.

Chapman University CS-510 Computing For Scientists Final Project

In this project, we will predict the price for AMES House and learn Machine Learning Algorithms, different data preprocessing techniques such as Exploratory Data Analysis, Feature Engineering, Feature Selection, Feature Scaling and finally to build a machine learning model.

Microservicio que predice la temperatura y humedad usando Arima y RandomForestRegressor

In this project we will predict the time taken by NYC taxis to complete their trips using regression.

Este trabajo se enfoca en la implementación de Limpieza, Análisis Exploratorio de Datos y Visualización de Datos para obtener conclusiones acerca del COVID-19 en Alemania.

This project focuses on developing a Machine Learning model to predict housing prices in California.

Steps to deploy a local spark cluster w/ Docker. Bonus: a ready-to-use notebook for model prediction on Pyspark using spark.ml Pipeline() on a well known dataset

Predicting House Prices with Random Forest Regression

Prepr's Machine Learning Challenge

Generated automated weekly sales forecast by departments in 45 stores using a dataset of weekly sales data spanning over 2 years, by employing the Random Forest Regressor model with achieving the Mean Absolute Error (MAE) of less than 10% of the forecast.

Cryptocurrency price prediction using Machine Learning, , aimed at aiding investors in making well-informed decisions by forecasting cryptocurrency prices across different timeframes in the dynamic and volatile market.

En este repositorio se almacenan los diferentes cuadernos utilizados a la hora de programar los algoritmos de ML utilizados para el estudio y realización del TFG

Car price prediction and its deployment

Analytics Vidhya hosts "JOB-A-THON" where over 7000+ enthusiasts got the opportunity to showcase their skills.