Almost 250 years after James Watt filed his first patent in 1769, we have reached a turning point in this new industrial revolution, as ecosystem evolutions enable a new wave of innovative products to come to life. Based on analysis of over 200 hardware startups, the HAX Hardware Trends Report has identified six key ways the world of connected devices has evolved and will impact our lives in the coming years.read more »
Big data analytics is quickly gaining adoption. Enterprises have awakened to the reality that their big data stores represent a largely untapped gold mine that could help them lower costs, increase revenue and become more competitive. They don't just want to store their vast quantities of data, they want to convert that data into valuable insights that can help improve their companies.
In this article find all the answers to the What, Why and How of Big Data Analytics.read more »
Chances are, your company is awash in a tsunami of data these days. And you’ve thrown everything from open-source databases to machine learning algorithms — as well as an army of data scientists — at the problem. But I bet if you asked your data scientists how effective those tools are, they’d say they can still barely keep afloat. This is exactly why businesses today need to kick the tires on deep learning — there is simply too much data, and too much variety, for smart peo..
Today, most banking, financial services, and insurance (BFSI) organizations are working hard to adopt a fully data-driven approach to grow their businesses and enhance the services they provide to customers. Like most other industries, analytics will be a critical game changer for those in the financial sector.
Though many BFSI organizations are beginning to disrupt their analytics landscapes by gathering immense volumes of data assets, these companies are at varying levels of Big Data maturit..
The Internet of Things is influencing nearly every aspect of our lives. Everything from our home appliances to traffic signals to our workplaces is connected to the Internet, and the network only continues to expand. It seems that no industry is left untouched by the IoT, and that includes healthcare.
In fact, some have even argued that healthcare is perhaps the best place for IoT applications.
This article is written for anyone who is considering becoming a data scientist. That includes young people just starting their bachelor’s degrees and folks in the first two or three years of their careers who want to make the switch.
It’s not for folks who know they are going to pursue one of the new Master’s in Data Science or Ph.D. candidates. It’s for folks looking for entry level jobs that are specifically on the data science career ladder.
Business volatility and the complexity of factors influencing demand are making it hard to reliably model the causes of demand variation. Traditionally, companies want to capture demand as close to the customer as possible, using inventory models to determine the appropriate product mix across the entire supply chain. Here are two basic principles behind the use of statistical models within the supply chain to accurately forecast demandread more »
The exuberance around A.I. technologies right now lends an exaggerated sense of newness to the field. The concept and the building blocks of A.I. are, in fact, decades old. And as the Forrester report points out, pure A.I. — computers that mimic or even exceed human intelligence — is still not reality.
Yet analysts and organizational executives say they’re increasingly harnessing A.I. and A.I.-related technologies (sometimes called pragmatic A.I.), such as machine learning, i..
In this article, we are going to learn how the logistic regression model works in machine learning. The logistic regression model is one member of the supervised classification algorithm family. The building block concepts of logistic regression can be helpful in deep learning while building the neural networks.Re..