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Data Scientist: Why it maybe the best career after college

October 27, 2016 by · Leave a Comment
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This infographic is proposed by Sandipan Pal.

Finally, the day has arrived.

After years of teaming up for group studies, setting goals and planning to fare better than your competition, you have achieved it.

Topped your grades and now waiting to make a mark in your field.

But, how do you make a mark?

Easier said than done, isn’t it?

Traditionally, it would mean following the “successful” people in your areas of interest and then walking on their path.

But what if you wish to pave your own path and build a career in something that interests you rather than following what others do?

And if a career in data science is what interest you, then you are at the right place.

See, there are many avenues to explore in data as a career.

Not only can basic knowledge of certain software languages help you to set a firm foot in the industry but will provide the much needed edge in marking a mark for yourself.

In fact, this infographic also enforces the growing demand for data scientists by clearly pointing out that not only are people extremely satisfied in the role of a data scientist but are also being paid equally well.

That means not only is there a demand for data scientist but if you keep yourself updated with the latest happenings in the industry then there is no looking back.

And what about making a mark?

Well, irrespective of whether you get into programming, work as a quality analyst, business analyst or even a digital analytic consultant each fall under the data scientist category and they will only open up more opportunities in this high demand market.

Go ahead and explore data scientist as a career!



How Analytics tools are shaping the growth story across industries

September 20, 2016 by · 3 Comments
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Today’s guest post is written by Mohammad Farooq

If there’s one thing that businesses across all industries have in common today, it’s in their increased adoption of data to shape business decisions. Below is a demonstration of how key industries use analytics tools and the benefits these tools have in solving challenges of data capture and use to shape growth.


Traditionally, insurers have relied on manual sampling of… Continue reading... | 3 Comments


Data Science Book Review: The Data Science Handbook

September 2, 2016 by · 7 Comments
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ds_handbookThe Data Science Handbook gathers 25 interviews of Data Scientists. Interviews are well done, most questions depending on the previous answer. This gives a nice feeling of discussion between the interviewer and the Data Scientist. On the content side, it provides interesting insights about the job of Data Scientist. The book is however biased towards pioneers in the field spending 14h… Continue reading... | 7 Comments


Data Science Book Review: Everydata

August 22, 2016 by · 1 Comment
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EverydataGoing opposite direction to the current Big Data trend, Johnson and Gluck discuss the little data we consume everyday in their book Everydata. The book is a fresh and easy reading. Through several practical examples, authors covers topics such as sample selection bias, correlation vs. causation and graphics (e g. how to play with plot axes).

Everydata is full… Continue reading... | 1 Comment


Data Science Book Review: The Business Forecasting Deal

July 24, 2016 by · 4 Comments
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9780470574430.pdfThere are not many books on forecasting. Even less good books. The Business Forecasting Deal, by Michael Gilliland, is one of them. The book is among the rare ones providing real practical advices for professionals. No theory, no equation, no code. The book focuses on typical forecasting challenges, misconceptions and issues when deploying processes into production. The main point of the… Continue reading... | 4 Comments


Data Science Book Review: Data Smart

June 21, 2016 by · 4 Comments
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DSmartIf you want to get started with Data Science and don’t like learning a new language such as R or Python, then this book is a perfect fit for you. Entertaining, Data Smart: Using Data Science to Transform Information into Insight approaches data science from a unusual angle. John W. Foreman has written a book for those who wants to apply… Continue reading... | 4 Comments


Gradient Boosting Machine – A Brief Introduction

June 1, 2016 by · 18 Comments
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treesOne of the Predictive Analytics projects I am working on at Expedia uses Gradient Boosting Machine (GBM). This is currently one of the state of the art algorithms in Machine Learning. This article provides insights on how to get started and advices for further readings.

I will now focus on the use of GBM for regression, based on decision trees… Continue reading... | 18 Comments


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