There are 1 repository under random-forest-regressor topic.
Learning to create Machine Learning Algorithms
The project aimed to implement Deep NN / RNN based solution in order to develop flexible methods that are able to adaptively fillin, backfill, and predict time-series using a large number of heterogeneous training datasets.
I have used Multinomial Naive Bayes, Random Trees Embedding, Random Forest Regressor, Random Forest Classifier, Multinomial Logistic Regression, Linear Support Vector Classifier, Linear Regression, Extra Tree Regressor, Extra Tree Classifier, Decision Tree Classifier, Binary Logistic Regression and calculated accuracy score, confusion matrix and ROC(Receiver Operating Characteristic) and AUC(Area Under Curve) and finally shown how they are classifying the tweet in positive and negative.
Machine Learning Software that predicts planets based on their distance from the sun, number of satellites and various properties
This project uses a machine learning approach in order to predict the number of goals scored by two teams in a match and then calculates the winning team
This is the proof of concept, how a relatively unsophisticated statistical model trained on the large MPDS dataset predicts physical properties from the only crystalline structure (POSCAR or CIF).
🌱 Predicting Number of Sales per Product 🌱
The aim of this project to see to do the prediction of the weather using the different types of machine learning model.
🌱 Predicting Ames House Prices 🌱
Proyek pertama predictive analytics untuk membangun model machine learning yang dapat memprediksi harga sewa rumah dan apartement di India.
Machine learning project to predict NYC property prices.
Using Spotipy (Spotify Api) and data science techniques, create a playlist with songs similar to user's top tracks.
In this project using New York dataset we will predict the fare price of next trip. The dataset can be downloaded from https://www.kaggle.com/kentonnlp/2014-new-york-city-taxi-trips The dataset contains 2 Crore records and 8 features along with GPS coordinates of pickup and dropoff
Sales Time Series Forecasting using Machine Learning Techniques (Random Forest, XGBoost, and Stacked Ensemble Regressor)
Predict the mileage per gallon (mpg) for cars
Aprendizaje automático en la celebración de contratos gubernamentales en Colombia.
Prediction on energy consumptions of the city of Seattle in order to reach its goal of being a carbon neutral city in 2050.
📈 Bitcoin Price Prediction using Random Forest Regressor 🧠
The Revolving Credit Behavior Modeling project analyzes revolving credit to facilitate flexible access to funds within a credit limit, assisting financial institutions in setting accurate pricing strategies by addressing risk factors like inflation and interest rates.
Random Forest Regressor used
A Study of the Effect of YouTube Tech Channels on the Revenue of Newly Released Devices
The Zomato Delivery Time Prediction Application is a machine learning-driven Flask web application designed to predict the estimated delivery time for food orders placed on the Zomato platform.
Prediction of Electricity consumption in Household Units by using Random Forest Regressor
A Machine Learning Model that predicts price of pre-owned cars using Linear Regression and Random Forrest Regressor.
Determining the housing prices of California properties for new sellers and also for buyers to estimate the profitability of the deal.
This repository contains the code and resources for a Car Price Prediction project.
Predict sales prices and practice feature engineering, RFs, and gradient boosting
This Repository consist of all the Jupyter Notebooks, Images and .CSV files of the tasks that were assigned during the Cognizant Artificial Intelligence Course hosted on Forage
Analysis and modeling of Spotify songs data to predict popularity score of tracks using audio features. Implements data visualization, preprocessing, feature engineering and machine learning with Python.
In this notebook, we will be performing machine learning on the Big mart sales dataset
Check out this Electricity price prediction model using python machine learning.In which i use RandomForestRegressor Algoritham to predict the data and also visualize(UI) using Streamlit
Explore the Essay Quality Prediction project—a machine learning model that predicts essay quality based on typing behaviors. Leveraging a Random Forest Regressor, this tool provides insights into writing processes. Connect with me on LinkedIn and find more projects on GitHub. Happy coding! 📝✨