code feat

"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

“ Data really powers everything that we do .” — Jeff Weiner In the 21st century, Data is one of the most valuable entity anyone can have! There is loads-and-loads of data generated everyday. And to process this huge amount of data we need people who have expertise in it, who by the way are called as Data Engineers. Data Engineer collects the raw data, process it for further use; but we need an Analytic process which will automatically predict the data based on the previous one. And here's how 'Machine Learning' comes into the picture. "Machine Learning allows us to make highly accurate predictions based on the Historical Dataset which is used to train the machine learning model." Today let us look at a similar ML model to predict the 'Salary' of Employees based on 'YearsofExperience'. (P.S: I've provided pdf link at the very bottom of this page for clear understanding) 1) import the required modules 2) read the csv file 3) plot the graph 4) us