Project on Heart Disease predictor through machine learning using sklearn library of python
Additional libraries used in this project are: 1)sklearn 2)pandas 3)matplotlib
Please ignore folder named ES102_Project. Open the folder with name ES102_Project(1). Files uploaded to the repository: 1)ES102_Project.py 2)ES102_Project.ipynb 3)heart.csv File (1) is the regular .py file of the code, File (2) is the .ipynb file which can be directly uploaded to google colab to run the program (Preferred method as this method doesn't require to install libraries), File (3) is the .csv file which stores the dataset from which data is retrieved to run the project successfully.
CREDITS:- Source (Dataset on Heart Disease): https://www.kaggle.com/ronitf/heart-disease-uci Learnt some basics about sklearn library from: 1) https://www.youtube.com/watch?v=pqNCD_5r0IU , 2) https://www.youtube.com/watch?v=bwZ3Qiuj3i8 Learnt somethings about Linear Regression from: https://youtu.be/erfZsVZbGJI Learnt matplotlib library from: Computer Science with Python by Sumita Arora Few other links that I visited for more information: 1) https://www.shanelynn.ie/python-pandas-read_csv-load-data-from-csv-files/ 2) https://scikit-learn.org/stable/modules/linear_model.html 3) https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LinearRegression.html