Summary: Even if you’re not big enough to have a full blown data science group that shouldn’t hold you back from benefiting from AI. The market has evolved so that there are now industry and process specific vertical applications available from 3rd party AI vendors that you can implement. There are just a few things to look out for.
Added by William Vorhies on October 23, 2018 at 7:30am — No Comments
Summary: How about we develop a ML platform that any domain expert can use to build a deep learning model without help from specialist data scientists, in a fraction of the time and cost. The good news is the folks at the Stanford DAWN project are hard at work on just such a platform and the initial results are extraordinary.
Added by William Vorhies on September 4, 2018 at 8:02am — No Comments
In last part we have seen the basics of Artificial intelligence and Artificial Neural Networks. As mentioned in the last part this part will be focused on applications of Artificial neural networks. ANN is very vast concept and we can find its…Continue
Added by Jayesh Bapu Ahire on August 25, 2018 at 9:00pm — No Comments
Around two decades ago, marketing existed as a soft function within organizations. There is no denying its importance, of course, but from an organizational perspective, it was a function hard to measure in terms of impact on the bottom-line. But then boomed the digital age, and with it, an advent of channels that came to be known as social media. And in its wake,…Continue
Added by Senthil Nathan R on July 1, 2018 at 11:30pm — No Comments
Video: How Cognitive Anomaly Detection Transforms Industrial Maintenance.
Added by Ronald van Loon on March 23, 2018 at 10:30pm — No Comments
Companies like Amazon, and Facebook are setting the standard for customer expectations and customer experience.
This includes everything from understanding the whole customer journey, defining the context and personalizing it, to ensuring the payment experience is seamless and frictionless without compromising…Continue
IoT devices are everywhere, but they aren’t just used for Smart City related technologies.
From Google Home, Fitbit, Apple iPhone, and Laptops, you are already using IoT devices everyday. In fact, Ericsson predicts that there will be 30 billion IoT devices in use around the world by 2023!
IoT devices are spanning industries…Continue
Added by Ronald van Loon on March 10, 2018 at 11:27pm — No Comments
As everyone knows Machine learning studies computer algorithms for learning to do stuff. We might, for instance, be interested in learning to complete a task, or to make accurate predictions, or to behave intelligently. The learning that is being done is always based on some sort of observations or data, such as examples…direct experience, or instruction. So in general, machine learning is about learning to do better in the future based on…Continue
Added by Jayesh Bapu Ahire on March 3, 2018 at 6:00am — No Comments
Although cognitive computing, which is many a times referred to as AI or Artificial Intelligence, is not a new concept, the hype surrounding it and the level of interest pertaining to it is definitely new. The combination of hype surrounding robot overlords, vendor marketing and concerns regarding job losses has fueled the hype into where we stand now.
But, behind the cloud of hype that is surrounding the technology currently, there lies a potential for increased…Continue
Added by Ronald van Loon on February 8, 2018 at 8:30pm — No Comments
Artificial intelligence or AI for short is the field of making computer think like humans by creating an artificial brain. Whatever the human can do intelligently is required to be moved into machines. The machine will just do what the human tells it and no more. For example, the human can sort numbers in an intelligent manner and so machines should be intelligent by sorting numbers like humans. To do this, there are a number of algorithms like bubble sort that allows the machine to think…Continue
DML stands for “Dynamical Machine Learning” (more in the book, “SYSTEMS Analytics for IoT Data Science”, 2017). This match is not surprising once you realize that DML & IoT are both based on the venerable Systems Theory. Let us dig deeper . . .
Consider IoT for industrial applications. A machine is instrumented with sensors, data are collected in real-time (or at intervals), communicated to the cloud where IoT Data Science…Continue
Added by PG Madhavan on September 11, 2017 at 12:30pm — No Comments
Who’s this article for:
This blog is intended for enterprise data analysts, line of business users, and data practitioners who work with qualitative and quantitative data in decision-making.
How enterprise currently use data science and business intelligence today
Quantitative analytics based on statistical models predict outcome with data models built from historical datasets using machine-learning algorithms
Added by Sing Koo on September 10, 2017 at 4:00pm — No Comments
Much of the recent AI revolution has been focused on automation through big data and/or sensors and feedback into neural networks. The resulting applications are highly valuable to businesses and consumers. They improve quality of life by optimizing labor and resources. However, these applications fall short when it comes to handling human reasoning. Much of the rationale behind the operation of these systems are implicitly embedded in the data.…Continue
Added by Sing Koo on June 22, 2017 at 11:30am — No Comments
The quarterly earnings call is a critical event for publicly traded companies. Each call serves multiple purposes. It is both an important source of information for investors and an opportunity for a company to present a narrative of operational performance, financial health, and strategic vision in their own terms. It’s also an ideal opportunity for executives seeking to manage and optimize outcomes.
The advent of AI makes it plausible for…Continue
Added by Sing Koo on May 25, 2017 at 12:30pm — No Comments
Added by Rekha Joshi on April 18, 2017 at 12:30pm — No Comments
Enterprise applications trending to adopt Machine Learning as their strategic implementation and performing machine learning deep analytics across multiple problem statements is becoming a common trend. There are variety of machine learning solutions / packages / platform that exist in market. One of the main challenges that the teams initially trying to resolve is to choose the correct platform / package for their solution.
Based on my limited…Continue
Reading some recent blogs, I sense a level of angst among Data Science practitioners about the nature of their field. What exactly IS Data Science - a question that seems to lurk just below the surface . . .
As a young field of study and work, it will naturally take time for a definition of Data Science to crystallize. In the meantime, see if this works for you . . .…Continue
In this blog I will be covering the basic understanding of a data science problem. To begin with I think before starting with any data science problem you should know about 2 key things:
Let’s look at the each of the…Continue