alihussainmeer Goto Github PK

beizer-curve

The code computes the value of micro

covid-realtime-dashboard-india-and-kashmir

This was a 4 hour sprint for doing data analysis on Covid in india and kashmir wherein we wmployed the use of various data scrapping techniques followed by some data transformations and later on by visualizing the data.

data-analysis-to-predict-the-co2-emission

We have a dataset which contains various features of the car based on which we predict the Carbon dioxide emission.

hello

Hello World for Python

helper-functions-for-rsa-algorithm

In order to apply RSA algorithm we have to evaluate various metrics which can consume a lot of time. Before explaining what this helper function will do

library-fine-calculator-for-north-campus-university-of-kashmir

This Fine calculator calculates the fine of our Library

linking-google-sheets-python-pandas-and-google-studio-for-effective-data-analysis

https://www.youtube.com/watch?v=7I2s81TsCnc&t=28s

marketing_method_selection_using_a-b_test_python

Evaluation using A/B testing and when to take action

node_app_deployment

predictive-analytics-for-customer-targeting-application-in-bank-telemarketing-scenario-

Throughout the world, banking institutions employ diverse marketing strategies to advertise their products, gain new customers and/or retain the old ones. Telemarketing is one such method utilized by banks where individual customers are contacted by bank representatives with offers. The work undertaken in the project deals with finding solution to such problems which may help to re-design telemarketing strategies. This can be done when telemarketing strategies are based on data science and machine learning methods which can predict the outcome- whether a customer will buy the product or not. The work focuses on the various aspects of the dataset and endeavors to come up with a structured approach to derive proper insights from the data that would help in solving problems which are similar to this. In the end extensive comparative analysis is presented to aid in the understanding of different classification algorithms and various performance parameters that were employed for this problem.

pycaret

An open-source, low-code machine learning library in Python