Summary: In the literal blink of an eye, image-based AI has gone from high cost, high risk projects to quick and reasonably reliable. C-level execs looking for AI techniques to exploit need to revisit their assumptions and move these up the list. Here’s what’s changed.
For data scientists these are miraculous times. We tend to think of miracles as something that occurs instantaneously but in our world that’s not quite so. Still the rate…Continue
Added by William Vorhies on March 4, 2019 at 9:41am — No Comments
Facial recognition technology was always a mythical concept that we thought could be a tool that could solve many of our problems but would never see the light of day. Today, facial recognition is everywhere and is a part of the everyday technology that we use. The…
Added by Abhimanyu on October 25, 2018 at 12:50am — No Comments
Summary: There are some interesting use cases where combining CNNs and RNN/LSTMs seems to make sense and a number of researchers pursuing this. However, the latest trends in CNNs may make this obsolete.
The main components of systems theory that readers might remember are “inputs,” “processes,” and “outputs.” The part that tends to get neglected is “feedback mechanisms.” These mechanisms tell the system the extent to which operations fit the environment. If there is lack of fitness, there is stress. One adaptive impulse is to make processes more complex and intelligent - i.e. sometimes described as the fight response. Another impulse is to give up and run away - i.e. the flight…Continue
The use of formal statistical methods to analyse quantitative data in data science has increased considerably over the last few years. One such approach, Bayesian Decision Theory (BDT), also known as Bayesian Hypothesis Testing and Bayesian inference, is a fundamental statistical approach that quantifies the tradeoffs between various decisions using…Continue
Added by Kostas Hatalis on March 15, 2018 at 12:00pm — No Comments
Shahab Sheikh-Bahaei, Ph.D.*
Principal Data Scientist
Machine Learning (ML) is closely related to computational statistics which focuses on prediction-making through the use of computers. ML is a modern approach to an old problem: predictive inference. It makes an inference from “feature” space to “outcome/target” space.…Continue
Machine Learning is being applied to almost everything these days, and the results are immaculate. With the introduction of Machine Learning APIs, developers don't have to train their own Machine Learning Algorithms, rather they can use these Machine Learning API's to create most interesting applications.
Recently, I red an article in which Ben Hubl applied Microsoft Cognitive Service Emotions API to do emotions analysis of video of Hillary and Trumps last debate. I was amazed to see…Continue
Probably like most people, I tend to recognize data as a stream of values. Notice that I use the term values rather than numbers although in practice I guess that values are usually numerical. A data-logger gathering one type of data would result in data all of a particular type. Perhaps the concept of “big data” surrounds this preconception of data of type except that there are much larger amounts. Consider an element of value in symbolic terms, which I present below: there is an index such…Continue
Added by Don Philip Faithful on December 10, 2016 at 9:30am — No Comments
When you upload photos to Facebook, have you noticed that the website already seems to know who's in them? It’s remarkable, and you can give the credit to big data. Face recognition software, like fraud detection and ad matching algorithms, draws on deep libraries of content in order to deliver the correct results. And these data collections are hard at work across the…Continue
Added by Larry Alton on November 22, 2016 at 6:16am — No Comments
Last year I started developing a Face Recognition model. I started with static pictures and using Wolfram Mathematica. This year I found out we can do the same job using OpenCV in Python, or creating specific filters in R and applying Weierstrass and Gaussian transformation.
There are lots of difficulties in recognizing faces of the same person, like: position, rotation of face, age, feeling, brightness, gamma, contrast, gamma, saturation, obstacles like hands,hair and so…Continue
Added by Rubens Zimbres on October 15, 2016 at 4:00am — No Comments
I have never been formally trained on how to deal with seasonality. But I wanted to take a moment to share my perspective based on experience, which I hope readers will find fairly straightforward. Some people use sales revenues in order to evaluate seasonal differences. I find it more desirable to analyze units sold if possible. A price increase resulting in slightly higher revenues does not in itself represent increased demand. Nor should discounted prices leading to reduced revenues…Continue
Added by Don Philip Faithful on August 23, 2015 at 5:19am — No Comments
When I returned to university to do a graduate degree, I was interested to discover how certain terms are subject to "intellectual interpretation." A word that I was asked to explain during one of my earliest classes was "ontology." Since this term was absent from my dictionary, I originally confused it with "oncology." I faintly recall that oncology involves the study of tumors. After consulting a few sources, I said that ontology is the study of how things come to exist or into being. I…Continue
Added by Don Philip Faithful on May 30, 2015 at 6:17am — No Comments
As humans, we navigate our lives largely by the recognition of patterns. These patterns include the sound of a mother’s voice, the appearance of a dangerous animal or poisonous food, the familiarity of kin, and the attraction to potential mates. Accurate pattern recognition is key to an animal’s survival and progress, and has allowed humans to become the socially complex and advanced species we are today.
It should come as no surprise that…Continue
Added by Sean McClure on September 29, 2014 at 9:01am — No Comments