Predict the output which should give a fair idea about the chances of admission for a student for a particular university

Overview

AdmissionPrediction

Predict the output which should give a fair idea about the chances of admission for a student for a particular university. This dataset was built with the purpose of helping students in shortlisting universities with their profiles. This dataset is created for prediction of Graduate Admissions from an Indian perspective.The dataset contains several parameters which are considered important during the application for Masters Programs. The parameters included are :

  1. GRE Scores ( out of 340 )
  2. TOEFL Scores ( out of 120 )
  3. University Rating ( out of 5 )
  4. Statement of Purpose and Letter of Recommendation Strength ( out of 5 )
  5. Undergraduate GPA ( out of 10 )
  6. Research Experience ( either 0 or 1 )
  7. Chance of Admit ( ranging from 0 to 1 )

Dataset

• Serial No.

• GRE Score- out of 340

• TOEFL Score- out of 120

• University Rating – out of 5

• SOP - Statement of Purpose(out of 5)

• LOR - Letter of Recommendation Strength(out of 5)

• CGPA (Undergraduate GPA

• Research- Research Experience(either 0 or 1)

• Chance of Admit- Ranging from 0 to 1

NOTE: For dataset you can connect with me on LinkedIn https://www.linkedin.com/in/arvind-sandhu-4825b3184 I'll be more then happy to help you out with any concern

Owner
ArvindSandhu
ArvindSandhu
Pandas-method-chaining is a plugin for flake8 that provides method chaining linting for pandas code

pandas-method-chaining pandas-method-chaining is a plugin for flake8 that provides method chaining linting for pandas code. It is a fork from pandas-v

Francis 5 May 14, 2022
To-Be is a machine learning challenge on CodaLab Platform about Mortality Prediction

To-Be is a machine learning challenge on CodaLab Platform about Mortality Prediction. The challenge aims to adress the problems of medical imbalanced data classification.

Marwan Mashra 1 Jan 31, 2022
Built various Machine Learning algorithms (Logistic Regression, Random Forest, KNN, Gradient Boosting and XGBoost. etc)

Built various Machine Learning algorithms (Logistic Regression, Random Forest, KNN, Gradient Boosting and XGBoost. etc). Structured a custom ensemble model and a neural network. Found a outperformed

Chris Yuan 1 Feb 06, 2022
Bottleneck a collection of fast, NaN-aware NumPy array functions written in C.

Bottleneck Bottleneck is a collection of fast, NaN-aware NumPy array functions written in C. As one example, to check if a np.array has any NaNs using

Python for Data 835 Dec 27, 2022
ZenML 🙏: MLOps framework to create reproducible ML pipelines for production machine learning.

ZenML is an extensible, open-source MLOps framework to create production-ready machine learning pipelines. It has a simple, flexible syntax, is cloud and tool agnostic, and has interfaces/abstraction

ZenML 2.6k Jan 08, 2023
Predict the income for each percentile of the population (Python) - FRENCH

05.income-prediction Predict the income for each percentile of the population (Python) - FRENCH Effectuez une prédiction de revenus Prérequis Pour ce

1 Feb 13, 2022
AtsPy: Automated Time Series Models in Python (by @firmai)

Automated Time Series Models in Python (AtsPy) SSRN Report Easily develop state of the art time series models to forecast univariate data series. Simp

Derek Snow 465 Jan 02, 2023
(3D): LeGO-LOAM, LIO-SAM, and LVI-SAM installation and application

SLAM-application: installation and test (3D): LeGO-LOAM, LIO-SAM, and LVI-SAM Tested on Quadruped robot in Gazebo ● Results: video, video2 Requirement

EungChang-Mason-Lee 203 Dec 26, 2022
Iterative stochastic gradient descent (SGD) linear regressor with regularization

SGD-Linear-Regressor Iterative stochastic gradient descent (SGD) linear regressor with regularization Dataset: Kaggle “Graduate Admission 2” https://w

Zechen Ma 1 Oct 29, 2021
A simple example of ML classification, cross validation, and visualization of feature importances

Simple-Classifier This is a basic example of how to use several different libraries for classification and ensembling, mostly with sklearn. Example as

Rob 2 Aug 25, 2022
Machine Learning Algorithms ( Desion Tree, XG Boost, Random Forest )

implementation of machine learning Algorithms such as decision tree and random forest and xgboost on darasets then compare results for each and implement ant colony and genetic algorithms on tsp map,

Mohamadreza Rezaei 1 Jan 19, 2022
A scikit-learn based module for multi-label et. al. classification

scikit-multilearn scikit-multilearn is a Python module capable of performing multi-label learning tasks. It is built on-top of various scientific Pyth

802 Jan 01, 2023
My capstone project for Udacity's Machine Learning Nanodegree

MLND-Capstone My capstone project for Udacity's Machine Learning Nanodegree Lane Detection with Deep Learning In this project, I use a deep learning-b

Michael Virgo 407 Dec 12, 2022
Deploy AutoML as a service using Flask

AutoML Service Deploy automated machine learning (AutoML) as a service using Flask, for both pipeline training and pipeline serving. The framework imp

Chris Rawles 221 Nov 04, 2022
Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow

eXtreme Gradient Boosting Community | Documentation | Resources | Contributors | Release Notes XGBoost is an optimized distributed gradient boosting l

Distributed (Deep) Machine Learning Community 23.6k Jan 03, 2023
Python bindings for MPI

MPI for Python Overview Welcome to MPI for Python. This package provides Python bindings for the Message Passing Interface (MPI) standard. It is imple

MPI for Python 604 Dec 29, 2022
The Ultimate FREE Machine Learning Study Plan

The Ultimate FREE Machine Learning Study Plan

Patrick Loeber (Python Engineer) 2.5k Jan 05, 2023
A unified framework for machine learning with time series

Welcome to sktime A unified framework for machine learning with time series We provide specialized time series algorithms and scikit-learn compatible

The Alan Turing Institute 6k Jan 06, 2023
As we all know the BGMI Loot Crate comes with so many resources for the gamers, this ML Crate will be the hub of various ML projects which will be the resources for the ML enthusiasts! Open Source Program: SWOC 2021 and JWOC 2022.

Machine Learning Loot Crate 💻 🧰 🔴 Welcome contributors! As we all know the BGMI Loot Crate comes with so many resources for the gamers, this ML Cra

Abhishek Sharma 89 Dec 28, 2022
Adversarial Framework for (non-) Parametric Image Stylisation Mosaics

Fully Adversarial Mosaics (FAMOS) Pytorch implementation of the paper "Copy the Old or Paint Anew? An Adversarial Framework for (non-) Parametric Imag

Zalando Research 120 Dec 24, 2022