Summary: GANs (Generative Adversarial Nets) originally thought to be a tool for inexpensively creating DNN training data have instead become the tools for creating deep fake images. However the deep fake technology is now finding uses in the commercial world and promises valuable results.
Added by William Vorhies on May 6, 2019 at 7:57am — No Comments
We propose a simple model-free solution to compute any confidence interval and to extrapolate these intervals beyond the observations available in your data set. In addition we propose a mechanism to sharpen the confidence intervals, to reduce their width by an order of magnitude. The methodology works with any estimator (mean, median, variance, quantile, correlation and so on) even when the data set violates the classical requirements necessary to make traditional statistical techniques…Continue
Naive Bayes is a deceptively simple way to find answers to probability questions that involve many inputs. For example, if you're a website owner, you might be interested to know the probability that a visitor will make a purchase. That question has a lot of "what-ifs", including time on page, pages visited, and prior visits. Naive Bayes essentially allows you to take the raw inputs (i.e. historical data), sort the data into more meaningful chunks, and input them into a formula. …Continue
Added by Stephanie Glen on April 25, 2019 at 10:00am — No Comments
Summary: There are several approaches to reducing the cost of training data for AI, one of which is to get it for free. Here are some excellent sources.
Added by William Vorhies on October 2, 2018 at 7:23am — No Comments
Monday newsletter published by Data Science Central. Previous editions can be found here. The contribution flagged with a + is our selection for the picture of the week. To subscribe, follow this link.
Added by Vincent Granville on May 5, 2019 at 10:00am — No Comments
Added by Diego Lopez Yse on April 30, 2019 at 2:17pm — No Comments
Added by Marco Tavora on May 1, 2019 at 4:57am — No Comments
Artificial Intelligence (AI) and the technologies associated with it have disrupted the market and created room for bigger and better opportunities. Based on the insights from the data, these technologies require a lot of trust and assurances. Since organizations are…Continue
Added by Ronald van Loon on May 3, 2019 at 10:30pm — No Comments
Added by Stephanie Shen on May 5, 2019 at 8:35am — No Comments
The concept of efficiency is not always easy to grasp. People go to work. They do their job. They follow the pace. What exactly is efficiency in the scheme of things? I think it is important to be able to distinguish between how hard different workers are working. It is not really possible to discuss efficiency if this kind of comparison is not performed. Improving efficiency is about getting more from a person or process. Therefore in order to determine whether or not efficiencies…Continue
Added by Don Philip Faithful on May 4, 2019 at 6:58am — No Comments
"AI will be the most defining technology for the banking industry."
-Ravi Narayanan, HDFC Bank
Such a comment, coming from an organization (HDFC) which has taken a gigantic leap in adopting conversational banking in the form Eva, India’s first AI bank agent, isn’t surprising. However, make no mistake, AI is being accepted globally as the new UI for banks to interact with their customers. Industry thought leaders increasingly agree that…Continue
Added by Mahesh Kumar CV on May 4, 2019 at 10:00am — No Comments
Machine learning gives us the ability to train a model, which can convert data rows into labels in such a way that similar data rows are mapped to similar or the same label.
For example, we are building SPAM filter for email…Continue
Added by Sergey Zelvenskiy on May 2, 2019 at 8:43pm — No Comments
Artificial intelligence (AI) seemingly has been discussed everywhere over the last few years, and now it’s made its way into the commercial insurance industry. Organizations are using AI and machine learning for everything from streamlining operations to offering more personalized care and better customer service. There is an increasing sense of urgency about getting started on the AI journey. The question is how. Do they develop a custom solution in-house or purchase a third-party solution…Continue
Added by Ji Li on May 2, 2019 at 3:00pm — No Comments
Added by satyajit maitra on April 30, 2019 at 6:00am — No Comments
This crash course features a new fundamental statistics theorem -- even more important than the central limit theorem -- and a new set of statistical rules and recipes. We discuss concepts related to determining the optimum sample size, the optimum k in k-fold cross-validation, bootstrapping, new re-sampling techniques, simulations, tests of hypotheses, confidence intervals, and statistical inference using a unified, robust, simple approach with easy formulas, efficient…Continue
It is a well-known fact that neural networks can approximate the output of any continuous mathematical function, no matter how complicated it might be. Take for instance the function below:…
Added by Marco Tavora on May 1, 2019 at 4:52am — No Comments
Did you ever have a concept that you knew was right, but just couldn’t find the right words to articulate that concept? Okay, well welcome to my nightmare. I know that Data Science and Design Thinking share many common characteristics including the power of “might” (i.e., that “might” be a better predictor of performance), “learning through failing” (which is the only way to determine where the edges of the solution really reside), and the innovation liberation…Continue
Added by Bill Schmarzo on April 28, 2019 at 11:54am — No Comments
Over 1,000,000 machine learning, AI, analytics and data science practitioners use our resources. Access high quality, relevant and proprietary content found nowhere else. Find solutions to your problems, or learn how to transition to a career in data science.…Continue
Added by Vincent Granville on February 20, 2019 at 5:00pm — No Comments
Added by Aiden Johnson on April 29, 2019 at 10:30am — No Comments