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… Continue reading... | 1 Comment
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... | 4 Comments
The 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... | 10 Comments
Going 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... | 2 Comments
There 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... | 5 Comments
If 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... | 5 Comments
One 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... | 100 Comments