Trump on the brink of'major war' with Iran as Ayatollah defies his nuclear red line It looks like paradise... but the Costa Rica resort where a surfing legend was murdered while living with girlfriend less than half his age is hiding a seedy underbelly Courtney Love's agony over Kurt Cobain'homicide' investigation: Insiders break silence about new probe My wife showed me her extreme kink on Pornhub... then she begged me to do the unthinkable: DEAR JANE Lindsey Vonn's Winter Olympics ski crash injury is'a lot more severe than a broken leg' with her'leg in pieces' after specialists suggested she may need amputation Nancy Guthrie sheriff insists her case is'far from cold' despite no leads, arrests, or DNA matches 18 days after disappearance Unseen trove of Alexander brothers photos revealed... as horrifying sex crimes trial is rocked by jury scandal Ukraine peace talks collapse in less than two hours as Zelensky says it is'not fair' Trump wants him to compromise and not Putin How I lost eight stone by filling up on THESE two foods - and not a fat jab in sight: I will forever be haunted by my wedding and honeymoon pictures, but now I'm nine-and-a-half stone and eating more than ever Police arrest boyfriend of girl who vanished without a trace as they believe he'heinously murdered her' JFK Jr's hunky love rival kept Carolyn Bessette coming back for more... now we've found silver-haired Baywatch star on a bus bench Secret'immovable' UFO is hiding in plain sight in purpose-built structure claims US congressman The sex complaints women are too afraid to tell their husbands: The position we dread, the mistake most men make... and our favorite sneaky trick Your choice of a cheap Zinfandel Rosé over an expensive Argentinian Malbec might reveal more about your personality than your palate, according to a new study. Researchers have found that traits such as extraversion, openness and neuroticism can indicate what type of plonk you prefer. They used AI to determine personality traits based on the reviews, and compared it to the strength of wine people were buying. Analysis revealed that people who score high in agreeableness and openness tend to go for wines with a higher alcohol content. These are usually perceived as being of higher quality and have a richer body and taste - for example a Cabernet Sauvignon, Malbec, Port or Sherry.

In machine learning (ML), machines--computer programs--learn and improve based on the assessment of historical data without being directed to do so. This process allows them to improve the accuracy of predictions or decisions they make. ML is part of the wider field of artificial intelligence. But, unlike AI which seeks to mimic human intelligence, ML is focused on a limited range of specific tasks. The ML concept is already being used in areas like drug discovery1.

The world comprises of data, many data. Data is mostly in the form of documents, music, videos, pictures, and many more. Apart from us, the people, data is generated from many other resources like mobiles, tablets, computers, and other devices. Traditionally, humans have analyzed data and adapted systems to change in data patterns. However, the volume of data surpasses the ability for humans to make sense of it and manually write those rules. Machine Learning brings the promise of deriving meaning from all of the data; it is an automated system that can learn from data and also the change in data to a shifting landscape.

These days machine learning is all the hype. Unfortunately, these algorithms are usually considered rather hard to interpret, leaving business stakeholders feeling queasy. I've seen analytics teams use these powerful tools to build exceptionally good models only to have them thrown in the scrap heap. People just didn't get them. And if they don't get them, they don't trust them.

The idea of storytelling is fascinating; to take an idea or an incident, and turn it into a story. It brings the idea to life and makes it more interesting. This happens in our day to day life. Whether we narrate a funny incident or our findings, stories have always been the "go-to" to draw interest from listeners and readers alike. For instance; when we talk of how one of our friends got scolded by a teacher, we tend to narrate the incident from the beginning so that a flow is maintained.

Let's pretend that we've been asked to create a system that answers the question of whether a drink is wine or beer. This question answering system that we build is called a "model", and this model is created via a process called "training". The goal of training is to create an accurate model that answers our questions correctly most of the time. But in order to train a model, we need to collect data to train on. This is where we begin.

Confidence interval is abbreviated as CI. In this new article (part of our series on robust techniques for automated data science) we describe an implementation both in Excel and Perl, and discuss our popular model-free confidence interval technique introduced in our original Analyticbridge article, as part of our (open source) intellectual property sharing. This is part of our series on data science techniques suitable for automation, usable by non-experts. The next one to be detailed (with source code) will be our Hidden Decision Trees. Figure 1 is based on simulated data that does not follow a normal distribution: see section 2 and Figure 2 in this article. Classical CI's are just based on 2 parameters: mean and variance.

Confidence interval is abbreviated as CI. In this new article (part of our series on robust techniques for automated data science) we describe an implementation both in Excel and Perl, and discuss our popular model-free confidence interval technique introduced in our original Analyticbridge article, as part of our (open source) intellectual property sharing. This is part of our series on data science techniques suitable for automation, usable by non-experts. The next one to be detailed (with source code) will be our Hidden Decision Trees. Figure 1 is based on simulated data that does not follow a normal distribution: see section 2 and Figure 2 in this article. Classical CI's are just based on 2 parameters: mean and variance.

Confidence interval is abbreviated as CI. In this new article (part of our series on robust techniques for automated data science) we describe an implementation both in Excel and Perl, and discuss our popular model-free confidence interval technique introduced in our original Analyticbridge article, as part of our (open source) intellectual property sharing. This is part of our series on data science techniques suitable for automation, usable by non-experts. The next one to be detailed (with source code) will be our Hidden Decision Trees. Figure 1 is based on simulated data that does not follow a normal distribution: see section 2 and Figure 2 in this article. Classical CI's are just based on 2 parameters: mean and variance.

Confidence interval is abbreviated as CI. In this new article (part of our series on robust techniques for automated data science) we describe an implementation both in Excel and Perl, and discuss our popular model-free confidence interval technique introduced in our original Analyticbridge article, as part of our (open source) intellectual property sharing. This is part of our series on data science techniques suitable for automation, usable by non-experts. The next one to be detailed (with source code) will be our Hidden Decision Trees. Figure 1 is based on simulated data that does not follow a normal distribution: see section 2 and Figure 2 in this article. Classical CI's are just based on 2 parameters: mean and variance.