vinay-alt / house_price_pred

House Price Prediction

This is a simple machine learning project which predicts the houses in the banglore city using model built with the logistic Regression Algorithm. This project aims to apply various Python tools to clean the data, to remove some outliers to make it ready to apply machine learning algorithm and prepare a model with it so that it can be used for prediction later.

Tech Stack

Client: HTML, CSS

Server: scikit-learn, numpy, pandas, flask, json, pickle

Softwares Used: Jupyter Notebook, Pycharm Community Edition, Sublime Text 3

Screenshots

Feedback

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Lessons Learned

Like almost every data science or machine leanring project the data that I have picked up from kaggle for this project was also very irregular, filled with null values, So the first learning I have got from this project was how the data is standardized and how to reduce the various anomalies in the dataset. I had not only to deal with null values from the dataset but also the text data was also needed convertion into numbers as a requirement of model training process. I also learned to reduce the outliers in the data

Deployment

Along with implementation of the project. Deployement is also important The project is deployed on heroku using github integration facility of heroku

visit : house price prediction

Run Locally

Run this project at your local system using git bash at whatever location you want.

Clone the project

  git clone https://github.com/vinay-alt/house_price_pred.git

Go to the project directory

  cd house_price_pred

Install dependencies

  pip Install -r requirements.txt

Start the server

  python App.py