• #OMGyes

    WHO WE ARE

    We’re a group of researchers, filmmakers, engineers, designers, educators and sexologists who are passionate about making an honest, practical resource about women’s pleasure. We wanted this information for ourselves and couldn’t find it! Just knowing that ‘everyone’s different’ isn’t as useful as knowing the specific ways we’re different and being able to discuss them.

    [...]

    Women’s sexual pleasure has hidden in the shadows for too long. It’s time to get it all out in the open.

    There’s so much that’s been left unsaid, unasked, and unknown. All because of a taboo that, we believe, will look absurd in a few decades—the same way taboos from the 1950’s about oral sex and homosexuality are absurd to us now. We want to accelerate that transition.

    OMGyes is an entirely new way to explore fascinating, useful and fun information that’s been uncovered in new research. Let’s lift the veil and take an honest look at the specific ways women actually find pleasure.

    [...]

    Scientists and researchers have uncovered the inner workings of almost everything in the world. But the only large-scale sex research that’s been funded has either been biological (the physiology of what happens in the body during sex) or behavioral (general activities without the details, like the percentage of women who have orgasms or use vibrators). So what about the actual techniques and insights that women across the world discover that lead to more pleasure? That was an uncharted frontier, when it comes to science and research.

    So we conducted the first-ever, large-scale peer-reviewed and published research to get the details. And, thanks to the success of OMGyes Season 1, we’ve launched Season 2 and continue to do more and more research, expanding and growing the evidence-based, human understanding of sexual pleasure.

    Trailer

    #sexuality #science #research #pleasure #taboo #transition #sex #women #gender #techniques #insights #information #honest #myth

    https://www.omgyes.com/en

    –-> added to metalist : https://seenthis.net/messages/911504

  • Busting 4 Common Myths About #tech Careers With Data
    https://hackernoon.com/busting-4-common-myths-about-tech-careers-with-data-7f50b61f8dd4?source=

    (Source)We all know a friend who works in tech. And they are usually doing quite well for themselves, probably started coding since the beginning of time and often seem to be spoilt with career choices. Or are they?Here are some common myths about careers in tech and how they hold up against data. The data used here comes from a developer survey by #stackoverflow, a website that a of developers frequent regularly. It’s a pretty comprehensive survey, with more than a hundred thousand responses from all over the world. Let’s get started!1. You either have to have a computer science college degree and/or be a coding genius from an early age to be in techEnrolment in computer science majors have spiked in numbers in the recent years all across the globe. At the same time, there’s tons of (...)

    #data-science #insights #data-visualization

  • Love #insights, not data.
    https://hackernoon.com/love-insights-not-data-b763bf902662?source=rss----3a8144eabfe3---4

    Here is how you should be using data instead.Photo by Ekansh Saxena on UnsplashI can’t go one day without reading about big data. Companies often proudly proclaim how they have access to millions of data points (well, not anymore since a certain Ivy League-brand brought disrepute to the whole story). In the zeal to think big, we often forget why we were looking at the data in the first place.We look at data to make decisions.That is it, nothing else. Businesses — large multinational corporations and tiny garage startups alike — look at data solely because it helps them make informed decisions.Companies are not run by analysts who pore over data everyday. They are run by leaders who use (a fraction of the) data for effective decision-making.So what should we be doing with data instead? My points (...)

    #big-data #startup #analytics #hypothesis

  • Is Excel 2018 going to be the game changer in data visualization? – DataVis Experts

    http://datavisxperts.com/excel-2018-and-datavis

    I am afraid not.

    Is Excel 2018 going to be the game changer in data visualization?

    Tech giant Microsoft recently announced a ton of new features that it would be adding to our old pal Excel. Perhaps its time and God knows Excel has waited long enough for a major upgrade. But what will this upgrade actually do? Will it really live up to the buzz its announcement stirred up? And what are these new data types that they are talking about? We will try to answer all these queries here. Let’s dive in !

    #datavisualisation #visualisation #excel

    • It is meant to take any list of data and then start to generate insights”. Spataro [Microsoft’s general manager for Office] also said, “It will look at combinations, charts, pivot tables and it will recognize those that are most interesting by looking at outliers, looking at trends in the data, looking at things that represent changes.” It is named #INSIGHTS as of now. And machine learning is also being incorporated into this in order to facilitate the ability to take data from other services using APIs.

      En fait, ce qu’on met maintenant sous le mot visualisation, c’est le processus de réflexion et d’interprétation des données dont celle-ci n’est que le résultat. Si, en plus, l’outil magique qui fait tout tout seul et pense pour vous intègre du machine learning, les #lendemains_qui_chantent, c’est pour… demain, enfin, pour la date de sortie d’Excel 2018.

      Si on retombe sur ses pieds, il faut comprendre que la lutte avec gg:sheets est féroce, notamment autour de l’interface de réalisation des graphiques pour laquelle gg avait pris une nette avance. Avance que M$ avait en partie rattrapée avec Excel 2016 où l’interface des graphiques proposait, déjà, des «   graphiques recommandés  » et incorporait de nouveaux types de graphique introduit par gg, comme le treemap. En forçant le trait, ce qui est (sera ?) nouveau, c’est que la «  recommandation  » se revendiquera d’une intelligence en boîte (le fameux ML…)

      btw #merci !