In my previous blog “How DevOps Drives Analytics Operationalization and Monetization”, I discussed the critical and complementary role of DevOps to operationalize and...
The Machine Learning Race is upon us. Every organization is seeking to outpace their competition by leveraging AI/ML to drive differentiation for their business. To win t...
Introduction Data science is a multidisciplinary blend of data inference, algorithm development, and technology in order to solve analytically complex problems. At the co...
Introduction One of the major reasons organizations migrate to the AWS cloud is to gain the elasticity that can grow and shrink on demand, allowing them to pay only for r...
I stumbled upon this book by chance, when searching for material about time series (probably the most interesting chapter in this collection.) The various chapters are ac...
There are plenty of resources on the Internet to learn linear algebra or to get a refresher, including our own tutorial (here). Below are three interesting books found on...
With the help of Natural Language Processing (NLP), AI solutions can automatically extract critical business insights and emerging trends from large amounts of structured...
Introduction Building data pipelines is a core component of data science at a startup. In order to build data products, you need to be able to collect data points from mi...
Here I want to present my new book on advanced algorithms for data-intensive applications named “Probabilistic Data Structures and Algorithms in Big Data Applicatio...