Data Science is a combination of data inference, algorithms, and technology that solves complex problems. The core of this technology is data that is initially raw, then is streamlined, and stored in a data warehouse. These vast amounts of data can help generate significant business values.…Continue
Added by Amit Dua on March 3, 2019 at 8:30pm — No Comments
Added by Vincent Granville on March 3, 2019 at 9:30am — No Comments
A schema is a conceptual framework. It can function as a lens through which to study data. When I was conducting research on workplace stress to do my graduate degree, I did so through the critical lens of social disablement. I applied a hierarchical schema to study stress constructed from prominent themes in social disablement. I associated stress with the loss of personal autonomy in the workplace. There was little doubt in my mind that I had chosen a highly “academic” focus for…Continue
Added by Don Philip Faithful on March 2, 2019 at 7:28am — No Comments
In the nascent field of Data Science, myths are abound. Here's my top 10, scoured from the internet (where better than to find a myth or two?).
This one is only part myth. Historically, women have been discouraged from entering the computing sciences for many reasons unrelated to talent (see my previous post,…Continue
This book presents a broad range of deep-learning applications related to vision, natural language processing, gene expression, arbitrary object recognition, driverless cars, semantic image segmentation, deep visual residual abstraction, brain–computer interfaces, big data processing, hierarchical deep learning networks as game-playing artifacts using regret matching, and building GPU-accelerated deep learning frameworks. Deep learning, an advanced level of machine learning technique…Continue
Added by Sanjiban Sekhar Roy on March 1, 2019 at 11:30pm — No Comments
This blog will cover the following “Future of Smart” initiative topics:
Added by Bill Schmarzo on March 1, 2019 at 7:30pm — No Comments
What data scientists do?
As per my personal perception, i do break data science down into three components:
(1) business intelligence, which is essentially about “taking data that the company has and getting it in front of the right people” in the form of dashboards, reports, and emails;