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Prediction dataset csv. Dataset for my flood prediction work.

Prediction dataset csv Dataset consists of 12 columns and 1259 rows. Outbrain Click Prediction. ipynb' Jupyter Notebook or Python script to execute the analysis step-by-step. In conclusion, our salary prediction model, trained on a well-preprocessed dataset, successfully predicts salaries based on various factors. It has 3 columns - "Position", "Level" and "Salary" and describes the approximate salary range for an employee based on what level he falls under. Apr 18, 2023 · The India Weather Forecast built a state-level standard rainfall forecast system using a multi-model ensemble approach with model outputs from five prominent worldwide NWP centers. csv at master · plotly/datasets Loan Default Prediction Dataset This table contains loan data with information on loan applicants' demographics, financials, and loan details. Flexible Data Ingestion. Preview. csv and can be used for reference or alternative analysis. This project aims to develop accurate models to forecast house prices, leveraging data analysis and machine learning algorithms for insightful predictions. Contains booleans to characterize the daily weather conditions as suitable for picnic (True) or not (False) for all 18 locations in the dataset. Stock-Price-Prediction-Using-Machine-Learning/ │ ├── dataset. Contribute to selva86/datasets development by creating an account on GitHub. - This dataset is created for prediction of Graduate Admissions from an Indian perspective. The dataset consists of 614 rows and 13 columns. Learn more You signed in with another tab or window. Disease Prediction based on Symptoms. Sep 6, 2022 · weather_prediction_picnic_labels. Download Open Datasets on 1000s of Projects + Share Projects on One Platform. Inspired by the methodology employed by renowned institutions such as the Centers for Disease Control and Prevention (CDC), this dataset aims to provide a reliable Disease prediction dataset based on blood samples Kaggle uses cookies from Google to deliver and enhance the quality of its services and to analyze traffic. It is Position_Salaries. These datasets are used to train Software Defect Prediction Models. Use a dataset that includes information about housing prices and features like square footage, number of bedrooms, etc. The model utilizes regression techniques such as linear regression and decision trees to estimate prices based on various features like crime rate, number of rooms, and property age. The objective is to build a predictive model that can accurately predict whether a loan application will be approved or not based on the other features in the dataset. Empowering farmers with data-driven insights for informed crop planning and resource allocation. Top. Nov 10, 2023 · To practice and learn about linear regression, it is essential to have access to good quality datasets. csv at master · fmspecial/Stroke_Prediction A comprehensive analysis and predictive modeling of the "Salary Data. Explore Popular Topics Like Government, Sports, Medicine, Fintech, Food, More. Customer first apply for home loan after that company validates the customer eligibility for loan. - kb22/Heart-Disease-Prediction 11 clinical features for predicting stroke events. csv and can be found here. - amandp13/Flood-Prediction-Model You signed in with another tab or window. They have presence across all urban, semi urban and rural areas. csv was collected from December 31, 2023 00:01:30 UTC to January 1, 2024 00:01:30 UTC. View . Focused on blood donation data, the model identifies potential donors likely to return, optimizing blood bank efficiency. test-data-a. These factors May 7, 2024 · 4. Blame. Contribute to anujdutt9/Disease-Prediction-from-Symptoms development by creating an account on GitHub. Pre-assigned grid point weights based on anomalous correlations (CC) between values observed and predicted are established for each element model using two seasonal datasets, and multi provision of appropriate CSV: GNU General Public License: Link: Maintenance of Naval Propulsion Plants Gas turbine process data for component decay state prediction. - nileshely/Mobile-Price-Prediction raw. It is a comprehensive weather dataset that Welcome to the "USA Housing Analysis and Prediction Price" repository! 🏡📊 This project focuses on exploring and analyzing a dataset containing various attributes related to housing in the USA. I have also provided a sample Python code you can use to train using these The candidate needs to predict the likelihood of a borrower defaul1ng on a loan using a machine learning model. The two datasets were separately used to compare how each classifier performed during model training and testing phases. The primary goal is to gain insights into the factors influencing housing prices and to build a predictive model for estimating property prices. Insert Classification Models/ Assignment Exercise/Project Part 2/healthcare-data set-stroke-data. Preparing Results: Store the PassengerId from the test data and the corresponding Survival predictions (0 or 1). If ICCR datasets are not currently available you will be directed to our foundation partners The dataset is curated by combining 5 popular heart disease datasets already available independently but not combined before. - Amasa614/College-Placement-Prediction-Models Using Machine Learning algorithms to predict the chances of Flood in the state of Kerala. The predictive model is built using machine learning algorithms, with an emphasis on data exploration, cleaning, and interactive user input. Learn more Predicting crop yield of 10 most consumed crops in The project involves training a machine learning model (K Neighbors Classifier) to predict whether someone is suffering from a heart disease with 87% accuracy. Learn more The ICCR datasets are categorised into the following 13 anatomical sites. In this research paper, we explore the application of ML to weather prediction. py # Streamlit app script ├── requirements. It involves data cleaning, manipulation, and statistical analysis to uncover trends and insights in weather patterns. Data Exploration: In-depth analysis of the Datasets used in Plotly examples and documentation - datasets/diabetes. Aspiring data scientists, researchers, and enthusiasts this dataset to uncover patterns and insights that contribute to a deeper understanding of successful college placements. We provide a novel dataset for Bankruptcy prediction related to the public companies in the American Stock market (New York Stock Exchange and NASDAQ). csv). The soil properties dataset includes detailed information such as specific locations identified by latitude and longitude coordinates, soil pH, soil color, surface soil composition, electrical conductivity, and a range of soil macro and micronutrients. Code. Mapping rainfall erosivity over India using multiple precipitation datasets. This capstone project at the Hamad Medical Center, Doha, Qatar, aims to create a predictive model using machine learning. A subset of the original train data is taken using the filtering method for Machine Learning and Data Visualization purposes. Rainfall dataset from year 1901 to 2015. - iamteki/diabetics-prediction-ml Dataset-First lets look at the dataset. csv was collected from January 10, 2024 16: The dataset comprises crucial parameters such as IQ scores, CGPA (Cumulative Grade Point Average), and placement status. Implements Support Vector Machine (SVM) and Random Forest algorithms in Python, including code, data preprocessing steps, and evaluation metrics. ipynb_ File . Complete analysis of Heart Disease UCI dataset. A comprehensive analysis and predictive modeling of the "Salary Data. Machine learning models for predicting diabetes using the Pima Indians Diabetes Dataset. 📊 Dataset: The weatherAUS. 🏡 House Price Prediction - India Project Overview This project leverages machine learning techniques to predict the sale prices of houses in India using the Kaggle "House Price India" dataset. py # Model training script ├── main. - Rainfall-Prediction/data/final-dataset. csv was collected from January 4, 2024 01:30:30 UTC to January 5, 2024 01:30:30 UTC. Originally from: National Institute of Diabetes and This repository contains the Cropped-PlantDoc dataset used for benchmarking classification models in the paper titled "PlantDoc: A Dataset for Visual Plant Disease Detection" which was accepted in the Research Track at ACM India Joint International Conference on Data Science and Management of Data Indian Rainfall Erosivity Dataset (IRED): National-scale assessment of rainfall erosivity over India using gridded precipitation datasets. csv at master · TanvirMahmudEmon/Rainfall-Prediction Mar 7, 2025 · Dataset Source: Healthcare Dataset Stroke Data from Kaggle. , Saharia, M. (2022). Content The dataset contains several parameters which are considered important during the application for Masters Programs. In this dataset, 5 heart datasets are combined over 11 common features which makes it the largest heart disease dataset available so far for research purposes. File metadata and controls. It can be used to analyze factors that contribute to loan default, assess creditworthiness, and develop predictive models to identify potential defaulters. Dataset: Outbrain Click Prediction. House Price Prediction in India" is a data-driven project aimed at providing valuable insights and predictive models for the Indian real estate market. to train a model that can predict the price of a new house - tecumang/House-P heart-disease-analysis heart-disease-prediction heart-disease-dataset heart-disease-classification heart-disease-model Updated Jul 24, 2021 Jupyter Notebook Contribute to Sethu-bharathi/Datasets development by creating an account on GitHub. The price of houses in a certain area depends on various factors. The company wants to automate the loan eligibility process (real time) based on Description: The dataset comprises 918 instances and 12 features related to cardiovascular health, aimed at predicting heart disease. train. All these datasets are obtained from the NASA promise dataset repository Renting Insights: House Rent Prediction Dataset with 4700+ Listings Kaggle uses cookies from Google to deliver and enhance the quality of its services and to analyze traffic. - armanfh22/Boston_house_price_prediction Harnessing Meteorological Insights: A Comprehensive Dataset for US Rainfall Prediction October 3, 2024 Exploring Sentiment: Trends in Public Attitudes Toward SpaceX and Space Exploration This repository contains a comprehensive analysis and prediction model for student performance based on a rich dataset (student-mat. test. test-data-b. - kb22/Heart-Disease-Prediction A machine learning model to predict house prices using regression techniques. Users can input gemstone features, and the model will provide price predictions. Aug 15, 2022 · These datasets were used to develop machine and deep learning classifiers to predict diabetes. csv) to build our predictive models. The Outbrain Click Prediction dataset deals with predicting what recommended content users will click next. - alavi-sam/salary-prediction A Comprehensive Dataset for Price Forecasting with 13 key Features. Open Datasets from the Omdena Community. csv Sep 4, 2024 · The dataset is comprehensive, encompassing various key factors critical to machine learning-based crop recommendation systems. Nov 19, 2024 · Running Predictions: Input the test dataset into the trained model to predict survival outcomes. png- Simple map showing all 18 locations in Europe. Each instance includes information such as the patient's age, sex, chest pain type, resting blood pressure, serum cholesterol levels, fasting blood sugar, resting electrocardiogram results, maximum heart rate achieved, presence of exercise-induced angina, ST Weather (Max-Planck-Institut Weather Dataset for Long-term Time Series Forecasting) The dataset includes information about loan applicants, such as their credit history, income, education, employment, and loan amount. weather_prediction_dataset_map. csv file is included in the project structure. We collected accounting data from 8262 different companies in the period between 1999 and 2018. Kaggle uses cookies from Google to deliver and enhance the quality of its services and to analyze traffic. This dataset is used to predict whether a patient is likely to get stroke based on the input parameters like gender, age, and various diseases and smoking status. This repository offers a comprehensive dataset, tools, and analyses to assist users in understanding and predicting house prices in different regions of India. txt # Python dependencies ├── README. The objective is to help potential buyers, sellers, and investors make informed decisions based on data The Loan Prediction dataset from Kaggle contains 614 loan applications with 13 features, including gender, marital status, income, loan amount, credit history, and loan status. - salary-prediction/Salary Data. This project predicts stroke disease using three ML algorithms - Stroke_Prediction/Stroke_dataset. Crop Yield Prediction Prediction. 2016: Signal: 16: R: 11. 934: : Synthetic: Non-Standard: More Information Use of this dataset in publications must be acknowledged by referencing the following publication: Crop Yield Prediction using Machine Learning: Models leveraging historical data, weather, and soil characteristics to forecast potential crop yield. Loan Approval Dataset used for Prediction Models. A collection of datasets of ML problem solving. The cardiovascular disease dataset is an open-source dataset found on Kaggle. Project Objective: This project aims to develop a web application that allows users to predict weather conditions for a specific location and date. Code Execution : Run the 'Analysis. - adamyak/Loan-Default-Prediction Machine Learning Project for Finance - Loan Repayment Prediction with Decision Tree - Loan_Repayment_Prediction/Loans_Dataset. A Comprehensive Dataset for Predicting Diabetes with Medical & Demographic Data Kaggle uses cookies from Google to deliver and enhance the quality of its services and to analyze traffic. The skewness in the data for the response is typical in medical datasets that deals with prediction of rare occurrences like stroke. It includes exploratory data analysis, cleaning, feature engineering, and modeling. The app then The crop recommendation dataset offers vital agricultural insights, including soil composition and environmental variables. Reload to refresh your session. Includes data preprocessing, feature engineering, and evaluation metrics. We then split the data into training and testing datasets in the ratio of (80:20). csv # Dataset used for training │ ├── model. Traffic Flow Prediction Using Historical Data This project predicts traffic flow based on vehicle counts (cars, bikes, buses, trucks), time, and day of the week. The data consists of 70,000 patient records (34,979 presenting with cardiovascular disease and 35,021 not presenting with cardiovascular disease) and contains 11 features (4 demographic, 4 examination, and 3 social history): StudentID,Age,StudyTimeWeekly,Absences,GPA,Gender,Ethnicity,ParentalEducation,Tutoring,ParentalSupport,ClubInvolvement,Sports,Music,Volunteering,GradeClass This salary prediction model can be used to make informed salary estimates based on individual characteristics, making it a valuable tool for HR analytics and compensation planning. csv - Optional data to be used as potential labels for classification tasks. md # Project documentation └── . You signed out in another tab or window. This project focuses on predicting loan approval outcomes through an extensive analysis of a curated dataset. Flight Delay Prediction: Building a predictive model analyzing flight delay in Indian Airlines by preparing data from scratch using APIs and web scraping methods. A research-based practice project where a model of traffic congestion prediction was constructed by using machine learning classification algorithm - random forest and Support Vector Regression. test-data-c. Acknowledgements The Data has been extracted from MagicBricks (a website, provides common platform to property buyer and seller ). Information about the crop yield of different crops, along with various environmental factors that affect the yield weather_prediction_picnic_labels. Apr 2, 2024 · The Symptom-Disease Prediction Dataset (SDPD) is a comprehensive collection of structured data linking symptoms to various diseases, meticulously curated to facilitate research and development in predictive healthcare analytics. It enables informed decisions to optimize crop yield, resource management, and sustainability in agriculture. Users can select a date from a calendar interface and choose a weather variable they are interested in, such as temperature, precipitation, or cloud cover. , Chakma, & Rafienasab, A. Predicting Credit Card Defaults This repository provides a step-by-step tutorial on predicting credit card defaults using machine learning algorithms in Python with scikit-learn. csv. Ideal for real estate analysis and decision-making. Both datasets are publicly accessible and can be cited as follows: P. Specifically, we focus on the use of supervised learning algorithms, including decision trees, logistic regression, and k-nearest neighbors, to predict weather conditions based on historical data. Data Import: Load the dataset using Pandas from the provided 'data. Predict Fllight Price, practise feature engineering, implement ensemble models The latest and complete IPL dataset (Updated till 2024 Season) IPL Complete Dataset (2008-2024) | Kaggle Kaggle uses cookies from Google to deliver and enhance the quality of its services and to analyze traffic. The project explores various aspects of students' academic, personal, and social life, aiming to understand the factors influencing their final grades and to predict academic outcomes. This repository contains 5 datasets, namely, KC1, JM1, CM1, KC2, PC1 in CSV and ARFF formats. You switched accounts on another tab or window. Learn more. It identifies traffic patterns, forecasts traffic situations, and provides insights to manage congestion, optimize traffic control, and reduce emissions for sustainable urban mobility. We pre-processed the data to handle missing values, outliers, and inconsistencies. The dataset encompasses a decade's worth of daily weather observations, including metrics like temperature, humidity, pressure, and wind speed. For example if an employee is a Manager - he falls in Level 4 and should get around $80,000. Edit . Saving the Output: Export the predictions to a CSV file for submission, with two columns: PassengerId: ID of each passenger from the The Mobile Price Prediction dataset comprises 836 entries detailing mobile phone specifications and prices across various brands, serving as a valuable resource for predicting mobile prices through data analysis. Dataset for my flood prediction work. . - NamrathaHV/Heart_Disease_Pre You signed in with another tab or window. 6 of the features are numerical valued and rest are categorical. Nov 6, 2020 · This heart disease dataset is curated by combining 5 popular heart disease datasets already available independently but not combined before. gitignore # Ignored files for Git DATASETS DATA TYPES DESCRIPTIONS Iris (CSV) Real Iris description (TXT) Wine (CSV) Integer, real Wine description (TXT) Haberman’s Survival (CSV) Integer Haberman description (TXT) Housing (TXT) Categorical, integer, real Housing description (TXT) Blood Transfusion Service Center (CSV) Integer Transfusion description (TXT) Car evaluation (CSV This Python project reads and analyzes weather data from CSV files using the Pandas library. We will always have many more examples of people without the condition, than with, making it very dificult to correctly identify the general pattern behind the minority class. Contains booleans to characterize the daily weather conditions as suitable for a picnic (True) or not (False) for all 18 locations in the dataset. The project involves training a machine learning model (K Neighbors Classifier) to predict whether someone is suffering from a heart disease with 87% accuracy. Hourly traffic data on four different junctions. csv: A dataset designed for testing the trained prediction model. Turney, Pima Indians diabetes data set, UCI ML Repository. Prediction of LogP from SMILES datasets of chemical molecules - kayneong/LogP-Prediction Forecasting rainfall using a comprehensive dataset from the Australian Bureau of Meteorology. House_price_prediction. Utilizing the House Prices Dataset , this project predicts home prices through a Jupyter notebook-based data science pipeline. It contains the code for data preprocessing, feature engineering, model training, and rainfall prediction using machine learning algorithms. System to predict whether a person has a heart disease or not based on the various biological and physical parameters. - ry4n-s/Rain-Prediction Use Machine Learning and Deep Learning models to classify 42 diseases ! 🏡 Boston House Price Prediction: A machine learning project that predicts housing prices in Boston using the famous Boston Housing dataset. csv: This dataset is used for training the machine learning This is the static test data from the study "Global Geolocated Realtime Data of Interfleet Urban Transit Bus Iding" collected by GRD-TRT-BUF-4I. Raj, R. It samples two billion page views, nearly 17 million clicks and a mess of user recommendations that were made across hundreds of publisher sites over the course of two Building a Machine Learning Model to Predict the Price of the Car By Comparing Performance of Different Regression Techniques (Simple Linear Regression, Multiple Linear Regression, Polynomial Regre Download Open Datasets on 1000s of Projects + Share Projects on One Platform. In this blog, we have compiled a list of 17 datasets suitable for training linear regression models, available in CSV or easily convertible to CSV (Excel) format. csv: This dataset is a slightly modified version of gemstone. csv" dataset to forecast salaries. csv' file. code for extracting Data is available at my Github account. Rainfall Prediction using Python from dataset in Bangladesh. csv at main · rocketingdatascience/Loan You signed in with another tab or window. csv at main · alavi-sam/salary-prediction Dream Housing Finance company deals in all home loans. We utilize the weather dataset (weatherAUS. You signed in with another tab or window. Contribute to n-gauhar/Flood-prediction development by creating an account on GitHub. Utilizes advanced machine learning techniques, including pipelines and transformers, for robust and accurate predictions. House Price Prediction Predicting house prices using machine learning based on factors such as size, number of bedrooms and bathrooms, lot size, and location (zip code). The five datasets used for its curation are: Cleveland We’re on a journey to advance and democratize artificial intelligence through open source and open science. Understanding the Code : Comments and markdown cells within the notebook explain each step and its purpose. - nileshely/Crop-Recommendation Stroke Predictions Dataset Part 4.