IPython Notebook best practices for data science

Поделиться
HTML-код
  • Опубликовано: 23 окт 2024

Комментарии • 10

  • @poosyful
    @poosyful 3 года назад +2

    Thank you, Mr. Jonathan, looking forward to an update when you get the chance to share.

  • @KUBKO17
    @KUBKO17 3 года назад +1

    Great video Jonathan. It is 2021 and it would great to see the updated panel from you on how your best practices evolved especially that there is nbviewer and voila now :)

  • @CraigHollabaugh
    @CraigHollabaugh 8 лет назад +5

    This is a great intro on how to use notebooks for teams. It hit all the topics that didn't know about, ha! Thanks.

    • @JonathanWhitmore
      @JonathanWhitmore  8 лет назад +6

      Glad you liked it! I've updated the ideas in this talk quite a bit and now have an O'Reilly screencast course where I develop the ideas more fully: shop.oreilly.com/product/0636920044260.do

    • @CraigHollabaugh
      @CraigHollabaugh 8 лет назад +1

      Thanks, I'll take a look

  • @MelGeorge
    @MelGeorge 8 лет назад

    Impressed by the flexibility the notebook offers. Will give it another shot. Thanks for the very informative talk!

  • @gloryths
    @gloryths 4 года назад

    Hi Jonathan. Great video. However i haven't understood exactly the main purpose of the Ipython Qt console (In Anaconda mainly) and how it can help you with the jupyter notebook. Good job man.

  • @yashwanthtelukuntla9031
    @yashwanthtelukuntla9031 5 лет назад

    my jupyter notebook is not connecting to python kernel will you help me in fixing it.

  • @mike_98058
    @mike_98058 7 лет назад

    I found the talk interesting, but the title misleading. While the ideas presented here represent a good, usable approach and may be a candidate for best practice, a consensus is needed before claiming the title.