A few years ago, it was extremely uncommon to retrain a machine learning model with new observations systematically. This was mostly because the model retraining tasks were laborious and cumbersome, but machine learning has come a long way in a short time. Things have changed with the adoption of more sophisticated MLOps solutions.
Added by Henrik Skogström on November 30, 2020 at 11:11pm — No Comments
Okay, I'm as mad as hell, and I'm not going to take this anymore! If data scientists are the modern-day alchemist who turn data into gold, then why are so many companies using leeches to monetize their data?
When I talk to companies about the concept of a “Chief Data Monetization Officer” role, many of them look at me like I…Continue
A recent Wall Street Journal article, entitled Coronavirus Pandemic Helps Speed More CIOs Toward Business Operations Accountability, observed:…Continue
Added by Howard M Wiener on November 30, 2020 at 8:00am — No Comments
Here I share my predictions as well as personal opinion about the pandemic. My thoughts are not derived from running sophisticated models on vast amounts of data. Much of the data available has major issues anyway, something I am also about to discuss. There are some bad news and some good news. This article discusses what I believe are the good news and bad news, as well a some attempt at explaining people behavior and reactions, and resulting consequences. My opinion is very different from…Continue
Added by Vincent Granville on November 29, 2020 at 10:30pm — No Comments
Augmented Reality is beginning to push the paradigms of previous expectations as the ability to recognize cards by appearance and orientation opens up the possibility of a new kind of gaming. The use of "magical" proxies to position 3D animations coupled with autonomous agent awareness opens up the possibility of card games with armies attacking…Continue
Added by Kurt A Cagle on November 29, 2020 at 7:30pm — No Comments
The pandemic has shown how vulnerable our supply chains are. A small interruption can bring a supply chain to a halt, which in today’s fast-paced world, is simply not acceptable. Customers are always expecting their product to arrive on time when ordered, and any delay in the…Continue
Network graphs play a large part in both computing and data science, and they are essential for working with (and visualizing) both semantic graphs and property graphs. Nearly thirty years ago, AT&T produced a set of libraries called graphviz which were designed to generate various types of printed output. Over the years, the library has been adapted for different platforms and roles, and today is still one of the most widely used network graph visualization tools around.
Added by Kurt A Cagle on November 29, 2020 at 2:00pm — No Comments
Recently, someone (not me) suggested in a tweet to Judea Pearl, let's have a Kaggle** competition on the topic of Causal AI. I love the idea, so I am trying to promote it with this blog post. Big Pharma could fund such a competition for much less than what they pay for a TV commercial, and the technical insights they might gain from this exercise might prove to be invaluable to the pharmaceutical industry.…Continue
Added by Robert R. Tucci on November 29, 2020 at 1:01pm — No Comments
Daphne Koller is the leader of a mega-startup (Insitro) that uses Machine Learning (do they use Causal Bayesian Networks???) to do drug research. She also co-founded Coursera with Andrew Ng, and she co-wrote with Nir Friedman a 1200 page book about Probabilistic Graphical Models (e.g., Bayesian Networks)
Judea Pearl won a Turing award (commonly…Continue
Added by Robert R. Tucci on November 29, 2020 at 1:00pm — No Comments
Humans don’t start their thinking from scratch every second. As you read this essay, you understand each word based on your understanding of previous words. You don’t throw everything away and start thinking from scratch again. Your thoughts have persistence.
Traditional neural networks can’t do…Continue
Added by Hitesh Dsouza on November 29, 2020 at 9:00am — No Comments
Citizen Data Scientists represent a new breed of business analysts – a group of individuals with diverse business responsibilities and training, who wield sophisticated analytical tools, and employ complex methods of analysis to improve business results – all without the training or assistance of data scientists or IT team members. Citizen Data Scientists are business users who leverage the knowledge…Continue
Added by Kartik Patel on November 28, 2020 at 12:03am — No Comments
This blog was originally written in 2012, and am republishing it because with the increased use of black box AI / ML models to power key operational decisions, these human decision-making traps need to be thoroughly and holistically addressed during the analytics definition stage to avoid the dangers of unintended consequences.
Organizations are looking to integrate big data and advanced analytics into their business operations in order to become more…Continue
Added by Bill Schmarzo on November 27, 2020 at 12:56pm — No Comments
“Robotic process automation is not a physical [or] mechanical robot,” says Chris Huff, chief strategy officer at Kofax. In fact, there is no presence or involvement of any robots in the automation software, as its name says.
RPA or Robotic Process Automation is an amalgamation of three factors:
Added by Amit Dua on November 27, 2020 at 1:21am — No Comments
Diversity and inclusion (D&I) increasingly are becoming a focus area for businesses. And it is not just because it is the right thing to do, but it also makes excellent business sense. According to McKinsey, the top quarter of companies on the diversity list were 33 percent more likely to be among the most profitable in their…Continue
Added by Aileen Scott on November 26, 2020 at 3:00am — No Comments
Added by Kurt A Cagle on November 25, 2020 at 7:30pm — No Comments
This article was written by Carlos E. Perez.
In this post I will explore further the characteristics of Artificial Intuition with the goal of describing a set of patterns that can aid us in formulating novel architectures for Deep Learning. In a previous post, I introduced the idea that there are two…Continue
Added by Andrea Manero-Bastin on November 25, 2020 at 2:00am — No Comments
This article was written by Matthew Hughes.
CS 106A is Stanford University’s introductory programming course. The module – which is also available to view on YouTube – introduces the fundamentals of coding in an accessible way, and lays the foundations for…Continue
Added by Andrea Manero-Bastin on November 25, 2020 at 2:00am — No Comments
Why developers prefer Google's Angular app development for their projects? Keep reading to find out!
Mobile app development is gaining popularity all over the world. Businesses are trying to incorporate this tech into their process in order to bridge the gap between the users and…Continue
Added by James Smith on November 25, 2020 at 1:38am — No Comments
Across industries and enterprises, AI has been the key growth driver, and this is mainly due to the services offered under this technology umbrella. Every industry is now witnessing enhancements in business processes, costs, and efficiency due to AI's introduction in their field. Depending on the industry, AI offers something unique and has helped the key decision-makers to make fast and accurate decisions based on various implementation solutions.…Continue
Added by Rishabh Sinha on November 24, 2020 at 3:30am — No Comments
Consistent asset health across many levels from cell sites to regions is critical to ensure uninterrupted operations for telecom operators. However, proactively identifying anomalous patterns like equipment malfunction remains a major challenge. Drawing on Subex’s deep implementation experience, this paper describes the chief steps necessary to deploy successful pattern detection solutions. It also examines some high impact use cases for pattern detection that have systematically delivered…Continue
Added by Avinash Udaykumar on November 24, 2020 at 12:00am — No Comments