Machine Learning is a hot topic for today’s technology and is rapidly growing day by day.
We are using it for our daily life applications without even knowing it. This series will present the diversified application of Machine Learning in Oil and Gas, Education, E-Commerce, and the Manufacturing industry.
Machine learning methods are used in a wide range of areas. In this post, I will discuss a few of the ways that machine learning is used within the education space – specifically K-12. Machine learning has the potential of making a significant impact in this space, so let’s look at some of those areas.
Few industries are as primed to be radically improved by Machine Learning as the Telecoms industry. About 1.5 trillion U.S. dollars is forecast to be spent globally on telecom services in 2018.
The AI market specifically for oil and gas is expected to reach USD 2.85 billion by 2022. It's growing fast as more companies realize the potential of the technology. Artificial intelligence is being used to discover new gas and crude oil sources, optimize various industrial processes such as the transport of raw oil and even make more positive environmental decisions. How are oil and gas companies putting AI technologies to use in today’s market? To break it down, we're going to take a look at the three most important sectors in oil and gas: upstream, midstream and downstream applications.
Introduction Access to and control of data is one of the biggest challenges faced by data analysts and data scientists. Creative, persistent analysts find ways to get access to at least some of this data but doing that efficiently in a way that is also standardized and centralized for everyone on the team is difficult.
Introduction: Prediction is a tricky business. You have to step outside of your comfort zone, your fainted vision of the world and see it thorough across all possible dimensions. In this series, we will discuss the future of “AI”, applications that are yet unexplored.
Introduction: Humans are wired to make tough decisions bringing all the context and principles to bear. Similarly, can devices apply the available information to make the right judgment calls? In this series, we shall discuss some ethical dilemmas faced by emerging technologies.