Analyzing traveler feedback on a newly opened airport in Asia, Ravi gives us a walkthrough of his approach to a specific sentiment analysis problem.
Forecasting demand for electricity is of immense importance both for researchers and for industry experts. By accurately forecasting demand, power suppliers can prevent overloads, and can operate more efficiently with a higher profit margin.
A detailed article on HR Analytics, explaining what it is, how it works, and how organizations can leverage it to improve their culture and effectiveness.
Linear programming is a mathematical problem solving technique widely used in various industries to optimize operations and is widely recognized as one of the core concepts of Operations Research. In this post, Professor Lahiri gives a summary of the technicalities of this method.
How Facebook's Ad Matching algorithm works and how marketers can use this knowledge to their advantage.
A Predictive-Descriptive Artificial Intelligence-based expert computer system predicts a Democratic landslide victory in the race for the White House in 2016.
K means clustering is a method that is often used in sentiment analysis. This post gives an overview of how to implement this method.
Machine learning is becoming a ubiquitous characteristic in all industries. As the world makes this transition, we explore the role of services, the applications of open algorithms, and the creation of IP in developing data products for diverse markets.
A brief overview of digital analytics and steps that digital analytics experts take to leverage data to improve business conversions.
How organizations can effectively hire and leverage Big Data talent, and how the internal structure of an organization can be tailored to fit the needs of a data-driven enterprise.
In this post, Jonathan Bloom gives a summary of the history of Artifiicial Intelligence, followed by a brief overview of how the underlying mechanics work.
An analysis on Hospital Inpatient Discharges data released by New York State in 2012. This post shows that open data can be as useful as proprietary data.
How the emerging sensor technologies and accurate GPS location determination is changing the way we drive, all with the help of machine learning.
How you can efficiently select the appropriate model for your data using various variable/model selection methods.
An introduction to the role of analytics in HR departments along with some examples of analytics and data mining in the area.
How prescriptive analytics is becoming more and more mainstream as new technologies are being developed, and what companies can do to take advantage of this movement.
How you can use Data Mining techniques to enhance your software development process and the various advantages of this approach.
The importance of predictive analytics in analyzing customer behavior and the potential value of incorporating temporal dynamics into predictive models.
AI will have a complex relationship with humans that will change over time: While certain jobs will become automated, AI is more often poised to augment human labor and decision-making. Longer-term, many applications will be designed to empower humans with non-human capabilities, memory, experiences, and knowledge. Many ethical, philosophical, cultural, societal, and business norms will be forced into re-assessment.
The future of AI and what it transpires into, lies in the hands of those controlling the characteristics that bind this innovation. We can now imagine and think of ideas which might have made you a laughing stock a few years ago. From a computer system playing chess with the masters to driverless cars, the possibilities associated with AI are many. Considering the high skill levels of machines with AI, the technology can be used in numerous fields to expand human capabilities, to optimize the use of resources, and to enhance productivity.
A brief summary about how the data-driven culture has evolved, and how businesses can take advantage of it.
Why Certifications Programs in Big Data and Data Science? In this very nascent field of big data where both