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
Machine Learning approach for quantifying detector distortion fields

DistortionML Machine Learning approach for quantifying detector distortion fields. This project is a feasibility study for training a surrogate model

Joel Bernier 1 Nov 05, 2021
An open source framework that provides a simple, universal API for building distributed applications. Ray is packaged with RLlib, a scalable reinforcement learning library, and Tune, a scalable hyperparameter tuning library.

Ray provides a simple, universal API for building distributed applications. Ray is packaged with the following libraries for accelerating machine lear

23.3k Dec 31, 2022
CobraML: Completely Customizable A python ML library designed to give the end user full control

CobraML: Completely Customizable What is it? CobraML is a python library built on both numpy and numba. Unlike other ML libraries CobraML gives the us

Sriram Govindan 14 Dec 19, 2021
A collection of interactive machine-learning experiments: 🏋️models training + 🎨models demo

🤖 Interactive Machine Learning experiments: 🏋️models training + 🎨models demo

Oleksii Trekhleb 1.4k Jan 06, 2023
A comprehensive set of fairness metrics for datasets and machine learning models, explanations for these metrics, and algorithms to mitigate bias in datasets and models.

AI Fairness 360 (AIF360) The AI Fairness 360 toolkit is an extensible open-source library containg techniques developed by the research community to h

1.9k Jan 06, 2023
Automated Machine Learning with scikit-learn

auto-sklearn auto-sklearn is an automated machine learning toolkit and a drop-in replacement for a scikit-learn estimator. Find the documentation here

AutoML-Freiburg-Hannover 6.7k Jan 07, 2023
A webpage that utilizes machine learning to extract sentiments from tweets.

Tweets_Classification_Webpage The goal of this project is to be able to predict what rating customers on social media platforms would give to products

Ayaz Nakhuda 1 Dec 30, 2021
Kaggle Competition using 15 numerical predictors to predict a continuous outcome.

Kaggle-Comp.-Data-Mining Kaggle Competition using 15 numerical predictors to predict a continuous outcome as part of a final project for a stats data

moisey alaev 1 Dec 28, 2021
Python factor analysis library (PCA, CA, MCA, MFA, FAMD)

Prince is a library for doing factor analysis. This includes a variety of methods including principal component analysis (PCA) and correspondence anal

Max Halford 915 Dec 31, 2022
ML-powered Loan-Marketer Customer Filtering Engine

In Loan-Marketing business employees are required to call the user's to buy loans of several fields and in several magnitudes. If employees are calling everybody in the network it is also very length

Sagnik Roy 13 Jul 02, 2022
Breast-Cancer-Classification - Using SKLearn breast cancer dataset which contains 569 examples and 32 features classifying has been made with 6 different algorithms

Breast-Cancer-Classification - Using SKLearn breast cancer dataset which contains 569 examples and 32 features classifying has been made with 6 different algorithms

Mert Sezer Ardal 1 Jan 31, 2022
Cool Python features for machine learning that I used to be too afraid to use. Will be updated as I have more time / learn more.

python-is-cool A gentle guide to the Python features that I didn't know existed or was too afraid to use. This will be updated as I learn more and bec

Chip Huyen 3.3k Jan 05, 2023
AutoOED: Automated Optimal Experiment Design Platform

AutoOED is an optimal experiment design platform powered with automated machine learning to accelerate the discovery of optimal solutions. Our platform solves multi-objective optimization problems an

Yunsheng Tian 107 Jan 03, 2023
Iris-Heroku - Putting a Machine Learning Model into Production with Flask and Heroku

Puesta en Producción de un modelo de aprendizaje automático con Flask y Heroku L

Jesùs Guillen 1 Jun 03, 2022
🎛 Distributed machine learning made simple.

🎛 lazycluster Distributed machine learning made simple. Use your preferred distributed ML framework like a lazy engineer. Getting Started • Highlight

Machine Learning Tooling 44 Nov 27, 2022
Iris species predictor app is used to classify iris species created using python's scikit-learn, fastapi, numpy and joblib packages.

Iris Species Predictor Iris species predictor app is used to classify iris species using their sepal length, sepal width, petal length and petal width

Siva Prakash 5 Apr 05, 2022
icepickle is to allow a safe way to serialize and deserialize linear scikit-learn models

icepickle It's a cooler way to store simple linear models. The goal of icepickle is to allow a safe way to serialize and deserialize linear scikit-lea

vincent d warmerdam 24 Dec 09, 2022
using Machine Learning Algorithm to classification AppleStore application

AppleStore-classification-with-Machine-learning-Algo- using Machine Learning Algorithm to classification AppleStore application. the first step : 1: p

Mohammed Hussien 2 May 02, 2022
SmartSim makes it easier to use common Machine Learning (ML) libraries like PyTorch and TensorFlow

SmartSim makes it easier to use common Machine Learning (ML) libraries like PyTorch and TensorFlow, in High Performance Computing (HPC) simulations and workloads.

A machine learning web application for binary classification using streamlit

Machine Learning web App This is a machine learning web application for binary classification using streamlit options this application contains 3 clas

abdelhak mokri 1 Dec 20, 2021