Users who bought this… Also bought this…‘, I consider this as the statement of this generation. There is not a single shopping application not showcasing this feature to gain more from the buyers. This rule is another by-product of Machine Learning. We humans always look for more similar things which we like for example if a reader starts to like a book of the specific genre say ‘biography’ he/she is leaned towards having more such similar books. And this is what we call…

We live in a world where the amount of data has increased on a large scale in various fields. Websites track user activities, marketers collect the customer’s purchasing history, so-called “Quantified-Selfers” collect the user’s sleeping patterns and heart rates, and so on.

With the availability of vast amounts of data, most industries have started focusing on leveraging valuable insights from it. Those insights can give businesses a competitive advantage in the market and…

     I always wondered how our life would have been if Google hadn’t been there. We depend on most of things from our personal to professional life on Google and it’s app. Not even a single day goes by without accessing any of these Google apps. Our life is partially dependent on Google. My Mom always use to say there are two world which exists One where they were born and raised a pre-google era and One where we are born in a post-google era. It has made our life easier, flexible and…

I finished the initial version of my second book Automated Data Science and Artificial General Intelligence. It is version 1.0 to get things started. I will work in this direction my entire life, there is a lot more to be done. Any feedback is welcomed, enjoy :)

Read at https://www.machinelearninggod.com/books.html…

In the first article of this series, I had touched upon key concepts and processes of Data Science. In this article, I will dive in a bit deeper. First, I will define what is Statistical learning. Then, we will dive into key concepts in Statistical learning. Believe me; it is simple.

As per …

In 2006, Clive Humbly, UK Mathematician, and architect of Tesco’s Clubcard coined the phrase “Data is the new oil. He said the following:

”…

Does Big Data mean Hadoop? Not really, however when one thinks of the term Big Data, the first thing that comes to mind is Hadoop along with heaps of unstructured data. An exceptional lure for data scientists having the opportunity to work with large amounts data to train their models and businesses getting knowledge previously never imagined. But has it lived up to the hype? In this article, we will look at a brief history of Hadoop and see how it stands today.

2015 Hype Cycle –…

(Source: https://gcn.com/articles/2016/09/07/epa-air-sensor-challenge.aspx)

One of the most significant characteristics of the evolving digital age is the convergence of technologies. That includes information management (databases), data…

The aviation industry is a sector involving high cost and security concerns. Analytics in this sector has huge potential, as varied data can be collected at each touch point showcasing customer interests. Crucial factors such as weather forecast should be critically analyzed using sophisticated tools to ensure passenger safety. A lot of logistics complexity also lies straight from building an aircraft to safe take–off and landing. Also, since customers pay the highest prices in this form of…

It is not a huge stretch to say that almost any industrial activity or even a private activity in the entire world is impossible without oil and gas. These resources are not only used in heat and power space but also in everyday items like Manufacturing, Apparel and Transportation. Oil & Gas is acting as a lubricant to smoothen the operation in several industries. However, Oil & Gas industry in itself has undergone most difficult phases in past compared to other industries. The…

"Information is the oil of the 21st century, and Analytics is the combustion engine."

The Volume, Variety and Velocity of data coming into your organization continue to reach unprecedented levels. This phenomenal growth means that not only…

Credit analytics is a way to arrive at creditworthiness of a business or an organization i.e. the ability of the Business or organization to meet its financial obligations. In technical terms, the crux of credit risk analysis lies in identifying the appropriate level of default risk associated with investment in a particular entity.…

This is a lesson  from one of our Data Science for Lawyers Workshops (Moderately Advanced). It is part of our Quantative Analysis in…

Open data repositories are valuable for many reasons, including:

(1) they provide a source of insight and transparency into the domains and organizations that are represented by the data sets;

(2) they enable value creation across a variety of domains, using the data as the “fuel” for innovation, government transformation, new ideas, and new businesses;

(3) they offer a rich variety of data sets for data scientists to sharpen their data mining, knowledge discovery, and…

The flood of articles, webinars, and conferences related to Big Data is generating its own "infoglut". Consequently, it is really helpful when you find resources that summarize many of the latest developments in one place -- a sort of "Cliff Notes" for Big Data.  Here are six meta-resources that I have found useful, plus one additional collection that I…

I recently added two new data analytics books from Pearson to my growing Data Science and Big Data stack:

1. "R for Everyone: Advanced Analytics and Graphics", by Jared Lander.…

With all of the discussion about Big Data these days, there is frequest reference to the 3 V’s that represent the top big data challenges: Volume, Velocity, and Variety. These 3 V’s generally refer to the size of the dataset (Volume), the rate at which data is flowing into (or out of) your systems (Velocity), and the complexity (dimensionality) of the data (Variety).  Most practitioners agree that…