There is no statistical test that assesses whether a sequence of observations, time series, or residuals in a regression model, exhibits independence or not. Typically, what data scientists do is to look at auto-correlations and see whether they are close enough to zero. If the data follows a Gaussian distribution, then absence of auto-correlations implies independence. Here however, we are dealing with non-Gaussian observations. The setting is similar to testing whether a pseudo-random…Continue
Added by Vincent Granville on December 2, 2020 at 4:30pm — No Comments
Summary: There is now sufficient experience among mid and large sized companies starting their AI journey to identify a single best practice for moving from AI experimentation to scale-up: the AI COE (Center of Excellence).
If you are a mid-sized business, government organization, or educational…Continue
Added by William Vorhies on December 2, 2020 at 3:18pm — No Comments
There are several narratives that permeate around AI today. It has great promise, but it is not without pitfalls. Many early adopters have invested millions, but remain unimpressed and discouraged by the lack of returns thus far.
With that said, and despite the challenges, the community has identified the problematic areas in the process, and a…Continue
Added by Kirsten Lloyd on December 2, 2020 at 10:00am — No Comments
Added by Avinash Udaykumar on December 1, 2020 at 8:07pm — No Comments
Lean Six Sigma continues to remain relevant as a way to improve business process capabilities. Artificial Intelligence and data analytics go hand in hand with Lean Six Sigma in terms of searching for truth in data to improve processes.
Lean Six Sigma practitioners and Data…Continue
Added by Logan berger on December 1, 2020 at 7:30am — No Comments
In an article I posted last week, How to Choose the Right Graph for Your Data (In One Picture),…Continue
Added by Stephanie Glen on November 30, 2020 at 11:30pm — No Comments
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
PCA is mathematically defined as an orthogonal linear transformation that transforms the data to a new coordinate system such that the greatest variance by some projection of the data comes to lie on the first coordinate (called the first principal component), the second greatest variance on the second coordinate, and so on. In other words, we convert a set of observations of possibly correlated variables into a set of values of linearly uncorrelated variables called principal components. To…Continue
Added by Shruti Nair on November 30, 2020 at 10:30pm — No Comments
With its 175 billion parameters and a massive corpus of data on which it is trained – GPT-3 is already enabling some innovative applications
But GPT-3 could help pave the way for a new way of developing AI models
The GPT-3 paper is called…Continue
Added by ajit jaokar on November 30, 2020 at 12:00pm — 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
Question 1 : So, let’s start with the obvious question. What is DevOps and why is it inevitable for today’s businesses to adopt?
Answer : DevOps at the end of the day, if you look at it from a higher level, it is really the automation of agile, a better way to perform application design, development and deployment. This is far superior…Continue
Added by Mehul Nayak on November 30, 2020 at 5:30am — 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 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
Added by Logan berger on November 29, 2020 at 3:30pm — No Comments
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 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