At Eradicate Diabetes We Process 1200 to 1500 Blood Reports a day. It takes about 10 mins per report to be read and blood marker values manually updated to DB by our dietitians. This translates to 200-300 hours wasted per day and 100,000 hours wasted per year. Plus manually reading and updating to DB had an error rate of 15-20%. The mission statement aims to address specific challenges Reading text & extracting information from handwritten images & handwritten text is quite d

Regression analysis is a form of predictive modelling technique which investigates the relationship between a dependent and independent variable. In simple words regression means using the relationship to find the best fit line or the regression equation that can be used to make predictions. There are many types of regressions such as ‘Linear Regression’, ‘Polynomial Regression’, ‘Logistic regression’ and others but in this blog, we are going to study “Linear Regression” in d

In this blog post, I would focus on Linear Regression, Multiple Linear Regression or say Multivariate Regression Linear Regression: Linear regression is a commonly and widely used of all statistical techniques for predictive analysis. These regression estimates are used to explain the relationship between one dependent variable and one or more independent variables. A relationship between the variables is based on the equation: Y= mx + b How does it help: It helps us to predi

Gestational Diabetes is a problem many women suffer from during pregnancy. This model is build to understand the preconditions of it and take precautions if any at early stage if symptoms are there from the very start. To do this GDM data is taken and exploratory data analysis is done. In Python: import pandas as pd import numpy as np df = pd.read_excel('../input/gdgdgdm/GDM.xlsx') EDA: Under EDA data is analyzed for features to be used for detecting and analyzing gestational

What? Extract questions and answers pairs from telegram chats? How is it possible? How to do it? These were some of the few questions that came up to my mind when this assignment was given to us as a part of a training course. It seemed impossible to me, because I never thought that I could extract chat history and manipulate the data. I never believed that it would be this easy to extract chat history and filter data using various criteria until I tried it out and saw the de

We all know that Python is the most popular programming language that has even made kids to start coding in a very easy and fun way. It’s easy and English-like syntax has made it a versatile language which is used in various fields all over the world. What makes Python versatile is the built-in data structures that are very simple to code and use on any type of data and manipulate the data according to our needs. First, let’s try to understand What Data structures are? Data S

Often, you’ll work with data in Comma Separated Value (CSV) files. Exporting a DataFrame to CSV and importing a CSV file is an important part of further work/tasks. To start, here are the following steps and genetic syntax that you may use to convert a DataFrame to CSV in the R language. Sometime one would like to save CSV in a particular location so here this blog also represents how to save a CSV file in a user select location and in the default directory. There are two way