Skip to main content

Posts

Showing posts from February, 2023

Stock Market using Python

 "The stock market is a device for transferring money from the impatient to the patient." - Warren Buffett Today we'll look into few ways for accessing the stock market. And we'll do this using Python ! Now, as we know that there are 2 stock exchange in India; BSE and NSE So we'll get the data from both! To begin with let's access the data from BSE first. (P.S: I certainly like the 2nd and the 3rd method to access stock market!) * So, to import the BSE data we need to " pip install bsedata ". => And then import the module, => Create an object to store the Driver Class => Then we need to do " getQuote('script_code')" where we need to provide a script code of a company which we need to access. Just like here we have given; => And from here we can see that the script code was for the company named "V-MART". But we can't remember all the script code hence we need to download this script file from the BSE websi

Predicting whether the bank will give loan to its customers based on their credit score (Logistic Regression)

"The best thing about data is that it tells a story." - Naveen Jain Today let's have a look at another machine learning model know as Logistic Regression. Logistic Regression is a statistical model where the outcome is predicted as binary such as YES or NO, based on the previous/train_dataset. ( Please open the images in a new tab or try to zoom-in ) import required models read your dataframe visualize your dataset create Logistic Regression model split your data into train and test dataset fit your train dataset into the regression model predict future values visualize your predicted values Github link for pdf:  click here