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Basic Level Projects

Project Preparing Power BI Dashboard

Power BI, a business intelligence and data visualisation application, allows you to use data from variety of sources to generate dynamic dashboards and analytical reports.

R - Shiny based app on Decision Tree

Shiny is a R package that enables the development of interactive web applications that may execute R code in the background.

EDA and Data Preprocessing Using Python

Exploratory data analysis (EDA) is a strategy or philosophy that uses a number of approaches (mainly graphical) to analyze data.

Practice Areas

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Road Accidents

Provide corporate governance, helping clients manage responsibilitie of running a corporam responsibilities financial field.

Health Care Law

Provide corporate governance, helping clients manage responsibilitie of running a corporam responsibilities financial field.

Family Law

Provide corporate governance, helping clients manage responsibilitie of running a corporam responsibilities financial field.

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2. R - Shiny based app on Decision Tree

Shiny is a R package that enables the development of interactive web applications that may execute R code in the background. Using Shiny, Dashboards are designed, interactive charts are included in R based documents, and standalone apps can be hosted online.

Shiny generates your code into the HTML, CSS, and JavaScript required to display your application on the web after you use R to develop a user interface and server. Any R calculation you can do on your desktop can be performed by the application because it is running R code on the backend.

In this Project you will be preparing a Decision Tree based Regression Tree and Random Forest and then we’ll be able to show results on the  web application. 

3. EDA and Data Preprocessing Using Python

Exploratory data analysis is the crucial process of doing preliminary analyses on data in order to find patterns, identify anomalies, test hypotheses, and double-check assumptions with the use of summary statistics and graphical representations. To put it another way, exploratory data analysis (EDA) is a strategy or philosophy that uses a number of approaches (mainly graphical) to analyse data.

Maximize understanding of a data collection, reveal underlying structure, extract crucial variables, find outliers and anomalies, test underlying hypotheses, build sparse models, and decide on the best factor settings. 

In this project we are going to take help of few datasets, there will be procedures to be followed in order to modify or encode data so that a computer can readily parse it, visualize it, understand the pattern of it so that our analysis is not biased to one particular sort of data and can extract the deeper insights out of it.