One article or paperIt is the generation of new data — the indirect discovery of unvolunteered truths about people — the makes machine learning predictions unethical? This HBR article investigates a few interesting cases.
One video or podcastYou explain to students the concept of statistical significance, and the next question often is…and now what? how do we make a decision? Statistical significance is not as trivial as looking at an arbitrary threshold. It’s a model that describes our inherent uncertainty about the world.
One bookDon’t get yourself fooled by statisticians. When it comes to statistics, plenty of otherwise great scientists — yes, even those published in peer-reviewed journals — are doing statistics wrong. This book helps you avoid the most common traps.
One line of code
def index(conn, params) do
current_user = Auth.current_user(conn)
admin? = Auth.admin?(conn)
page = ElixirStatus.Persistence.Posting.published(params, current_user, admin?)
assigns = [
just_signed_in: params["just_signed_in"] == "true",
referred_via_elixirweekly: params["ref"] == "elixirweekly",
current_posting_filter: params["filter"] |> nil_if_empty(),
search: params["q"] |> nil_if_empty(),
|> render("index.html", assigns)
You are under no obligation to remain the same person you were a year ago, a month ago, or even a day ago. You are here to create yourself, continuously.Richard Feynman