An end-to-end regression problem of predicting the price of properties in Bangalore.

Overview

Bangalore-House-Price-Prediction

An end-to-end regression problem of predicting the price of properties in Bangalore. Deployed in Heroku using Flask.

Link for the web app: https://bangalore-house-estimate.herokuapp.com/

Demo

1 You go to the link given above, enter the requested values and click on the 'Submit' button below.

house ui

  1. The web app produces a prediction on the price.

house prediction

You might also like...
 PAWS 🐾 Predicting View-Assignments with Support Samples
PAWS 🐾 Predicting View-Assignments with Support Samples

This repo provides a PyTorch implementation of PAWS (predicting view assignments with support samples), as described in the paper Semi-Supervised Learning of Visual Features by Non-Parametrically Predicting View Assignments with Support Samples.

SkipGNN: Predicting Molecular Interactions with Skip-Graph Networks (Scientific Reports)
SkipGNN: Predicting Molecular Interactions with Skip-Graph Networks (Scientific Reports)

SkipGNN: Predicting Molecular Interactions with Skip-Graph Networks Molecular interaction networks are powerful resources for the discovery. While dee

 Predicting Semantic Map Representations from Images with Pyramid Occupancy Networks
Predicting Semantic Map Representations from Images with Pyramid Occupancy Networks

This is the code associated with the paper Predicting Semantic Map Representations from Images with Pyramid Occupancy Networks, published at CVPR 2020.

We are More than Our JOints: Predicting How 3D Bodies Move

We are More than Our JOints: Predicting How 3D Bodies Move Citation This repo contains the official implementation of our paper MOJO: @inproceedings{Z

A DNN inference latency prediction toolkit for accurately modeling and predicting the latency on diverse edge devices.

Note: This is an alpha (preview) version which is still under refining. nn-Meter is a novel and efficient system to accurately predict the inference l

A geometric deep learning pipeline for predicting protein interface contacts.
A geometric deep learning pipeline for predicting protein interface contacts.

A geometric deep learning pipeline for predicting protein interface contacts.

Implementation of Enformer, Deepmind's attention network for predicting gene expression, in Pytorch
Implementation of Enformer, Deepmind's attention network for predicting gene expression, in Pytorch

Enformer - Pytorch (wip) Implementation of Enformer, Deepmind's attention network for predicting gene expression, in Pytorch. The original tensorflow

Predicting path with preference based on user demonstration using Maximum Entropy Deep Inverse Reinforcement Learning in a continuous environment
Predicting path with preference based on user demonstration using Maximum Entropy Deep Inverse Reinforcement Learning in a continuous environment

Preference-Planning-Deep-IRL Introduction Check my portfolio post Dependencies Gym stable-baselines3 PyTorch Usage Take Demonstration python3 record.

Predicting lncRNA–protein interactions based on graph autoencoders and collaborative training

Predicting lncRNA–protein interactions based on graph autoencoders and collaborative training Code for our paper "Predicting lncRNA–protein interactio

Owner
Shruti Balan
Aspiring Data Scientist. Loves playing with data. Looking for exciting opportunities in the field. Fingers crossed!
Shruti Balan
🐤 Nix-TTS: An Incredibly Lightweight End-to-End Text-to-Speech Model via Non End-to-End Distillation

?? Nix-TTS An Incredibly Lightweight End-to-End Text-to-Speech Model via Non End-to-End Distillation Rendi Chevi, Radityo Eko Prasojo, Alham Fikri Aji

Rendi Chevi 156 Jan 9, 2023
Problem-943.-ACMP - Problem 943. ACMP

Problem-943.-ACMP В "main.py" расположен вариант моего решения задачи 943 с серв

Konstantin Dyomshin 2 Aug 19, 2022
null 5 Jan 5, 2023
Quantile Regression DQN a Minimal Working Example, Distributional Reinforcement Learning with Quantile Regression

Quantile Regression DQN Quantile Regression DQN a Minimal Working Example, Distributional Reinforcement Learning with Quantile Regression (https://arx

Arsenii Senya Ashukha 80 Sep 17, 2022
Hitters Linear Regression - Hitters Linear Regression With Python

Hitters_Linear_Regression Kullanacağımız veri seti Carnegie Mellon Üniversitesi'

AyseBuyukcelik 2 Jan 26, 2022
Official repository for "Intriguing Properties of Vision Transformers" (2021)

Intriguing Properties of Vision Transformers Muzammal Naseer, Kanchana Ranasinghe, Salman Khan, Munawar Hayat, Fahad Shahbaz Khan, & Ming-Hsuan Yang P

Muzammal Naseer 155 Dec 27, 2022
Explainer for black box models that predict molecule properties

Explaining why that molecule exmol is a package to explain black-box predictions of molecules. The package uses model agnostic explanations to help us

White Laboratory 172 Dec 19, 2022
Graph Self-Supervised Learning for Optoelectronic Properties of Organic Semiconductors

SSL_OSC Graph Self-Supervised Learning for Optoelectronic Properties of Organic Semiconductors

zaixizhang 2 May 14, 2022
TUPÃ was developed to analyze electric field properties in molecular simulations

TUPÃ: Electric field analyses for molecular simulations What is TUPÃ? TUPÃ (pronounced as tu-pan) is a python algorithm that employs MDAnalysis engine

Marcelo D. Polêto 10 Jul 17, 2022
This repository contains the code used for Predicting Patient Outcomes with Graph Representation Learning (https://arxiv.org/abs/2101.03940).

Predicting Patient Outcomes with Graph Representation Learning This repository contains the code used for Predicting Patient Outcomes with Graph Repre

Emma Rocheteau 76 Dec 22, 2022