BLOGS

Data Science

Data Science: All you need to know

A multidisciplinary fuse of data inference, algorithm development, and technology to solve analytically complex problems is known as Data science.Data science is eventually about using this data in creative ways to generate business value.Data Science is divided into two sub plots.1.Discovery of data insight which helps quantitative data analysis to help steer strategic read more..

• BY: RONIL PHILIPS
• Jan 10 2017

AI/Machine Learning

R AND PYTHON: GRADIENT DESCENT

My previous blog, I presented syntactical differences and similar functions between R & Python. Now, I want to take it to next level and write some machine learning algorithms using both R and Python. Here, one may use direct functions from the packages available. However, here I am presenting the way to write your own functions for algorithms. In this series, I am starting with Gradient de read more..

• BY: GANESH M
• Dec 28 2016

Recruiting Strategy

How to Source Candidates Like a Pro: Advanced Sourcing Strategies for Recruiters

In the realm of talent acquisition, addressing specialized requirements can be a daunting task. The frustration of not finding candidates who align perfectly with your client's needs is all too familiar. While traditional job portals like Monster, Dice, and Career Builder have been the go-to platforms, the question remains: How can we source candidates more ef read more..

• BY: Dushyant Sikligar
• Nov 08 2016

Recruiting Strategy

Mastering the Art of Skype Job Interviews: Tips for Success in the Virtual Job Market

Skype interviews have become a familiar and highly effective tool for significant clients and employers in today's fast-paced job market. This modern approach offers unparalleled convenience for both job seekers and hiring managers, especially when considering staffing needs and staff augmentation

• BY: Kaushal Dave
• Nov 08 2016

This & That

MASTERING EMAIL ETIQUETTE: 10 KEY CONSIDERATIONS FOR EFFECTIVE COMMUNICATION

For a considerable amount of time, many have predicted the demise of email. While it's true that we now use various forms of communication, such as messaging, video calls, and social media, to interact with friends and send quick messages to colleagues, email still holds a critical role, especially in professional communication and job applications. The import read more..

• BY: Bakul Purabia
• Oct 20 2016

Data Science

Battle of the Programming Languages: R vs Python

We are going to compare Functions exist in both R and Python for same operations. And for this we took the Titanic dataset which contains the Passenger details.Importing a CSVReading Data in both the languages is similar, but the only difference is for python we have to import pandas library for reading the Data. Once the importing is done we can look into the data read more..

• BY: GANESH M
• Oct 10 2016

Data Science

Modern Data Scientist: Technical and Soft Skills You Need to be successful

What skills are required to be a Data Scientist?ORIs strong mathematics background required to pursue a career as a data scientist?We at Rang Technologies see a lot of questions like this. It's hard when you're trying to break into the field to know exactly how much math & stats you need.Primarily, it depends on how a company is defining "

• BY: BAKUL PURABIA
• Sep 15 2016

Data Science

Retail banking classification models

Now days the retail banking is one of the important business in banking sector, to improve the customer base, retain the existing customer, improve the banking revenue by offering different product to customer.Today's world is digital, data is raising like population and you have to identify different customer in term of market opportunity, their risk and profit for bank.Of co read more..

• BY: BHARAT WARULE
• Aug 30 2016

Data Science

Key of Developing R Code: Batch Forecasting

Forecasting is a common technique used in several companies to make predictions for the future. There are multiple methods of forecasting such as time series forecasting, multivariate forecasting, etc. In each of these methods there are techniques such as Moving Average (MA), ARIMA, ARMA, ARCH, GARCH, etc.There are several packages and algorithms available for forecasting in every d read more..

• BY: SATISH KUMAR SIMHADRI
• Jul 21 2016

Data Science

R Package dplyr Comparison of functions

In R, you can accomplish the same task in different ways.This R document explains functions from R package--dplyr and in some places compares those functions with base functions.   # import dplyr library# we are going to work with R in built dataset airqualitylibrary(dplyr)head(airquality)   read more..

• BY: SANTHOSH SUBRAMANIAN
• Jul 12 2016

Recruiting Strategy

Unlocking Success in Recruitment: The Art and Science of Finding the Perfect Fit

Are you a dedicated recruiter with a passion for excellence? In the ever-evolving landscape of Mathematics and Science, recruiting and staffing services have undergone a significant paradigm shift. Traditional methods, such as sourcing and submitting resumes from online portals, often need to catch up in today's dynamic environment.

• BY: Pranav Patel
• Jul 01 2016

Recruiting Strategy

Crafting an Effective LinkedIn Profile for Recruiters: Best Practices and Tips

Your LinkedIn profile can be the key to establishing a strong recruiter brand identity. It serves as a platform for job seekers to discover you even before they have a conversation with you. Similarly, you can leverage LinkedIn profiles read more..

• BY: Pranav Patel
• Jun 20 2016

Recruiting Strategy

Avoid These Four Common Resume Mistakes and Boost Your Career Opportunities

Having spent years reviewing countless resumes, initially as a General Manager overseeing operations for multinational corporations and more recently as a Business Development professional at Rang Technologies in the Recruiting and Staffing industry. I've noticed a recurring pattern of avoidable mistakes that executive candidates make. These missteps often cos read more..

• BY: Pranav Patel
• Jun 03 2016

Clinical

BINOMIAL ENDPOINTS IN CLINICAL TRIAL AND GETTING 95% CONFIDENCE INTERVAL

There are various types of endpoints designed to get meaningful conclusion in clinical trial. These endpoints can be   Continuous E.g. Change from baseline in blood sugar after 6 month of treatment   Binary - E.g. Response or no response   Time to event - E.g. Time read more..

• BY: KAMLESH PATEL
• May 25 2016

Clinical

PATIENT PROFILE AND PATIENT SAFETY NARRATIVES

Patient profile is a listing of all (or selected, sometime) data for individual subject in clinical study organized by time. Subject can be patient or healthy volunteer, though it is referred as Patient Profiles. Patient profiles are optional in submission to FDA.However, patient profiles were recommended to submit in pdf file in CRT (Case Report Tabulation) to FDA previously (as pe read more..

• BY: KAMLESH PATEL
• Apr 25 2016

Data Science

Analytics Careers with SAS & R - Part 2

It's been a month and what a month it has been! The new year is here already! One wonders where all the time has gone! I hope you also wonder on how far you have come in the process of learning and equipping yourself towards a successful career and life and take pride in it! This 'present' day's effort will grant you the 'gift' of future!When we last communicated, we spoke of where read more..

• BY: SATISH KUMAR SIMHADRI
• Apr 15 2016

Data Science

Analytics careers using SAS and R : Part-1

Wikipedia describes Analytics as "the discovery and communication of meaningful patterns in data." This comes in handy especially in areas rich with recorded information. Every day companies all over the world collect data about their customers and industries, simply as a routine activity during business transactions.World-class firms use this collected data and leverage on analytic read more..

• BY: SATISH KUMAR SIMHADRI
• Apr 10 2016

Clinical

SAS LOG: ERROR, WARNINGS, NOTES -HOW TO MANAGE THEM?

SAS Clinical Solutions Let's continue SAS Clinical Solutions with SAS log's ERROR, Warning and Notes handling. We show in previous blog about ERRORS and now, let's discuss on WARNINGS and NOTES*********************WARNING************************;a. WARNING: Multiple lengths were specified for the variable state by input data set(s). This may ca read more..

• BY: KAMLESH PATEL
• Feb 28 2016

Data Science

YOU ARE JUST 3 STEPS AWAY FROM BECOMING A SUCCESSFUL DATA ANALYST

What the hottest topic in today's business world? Data! What does every business need in order to analyze trends and make informed decisions? Data! On what basis are key policies framed that can make or break our modern world? Data again! Sounds interesting?! Imagine being involved in data analysis at some level and enabling businesses make such key decisions... if this is something you would l read more..

• BY: KAMLESH PATEL
• Dec 05 2015