DataCamp/Coiled Live Coding: Data Science and Machine Learning at Scale

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On this stay code-along session, Hugo Bowne-Anderson, Knowledge Scientist and Head of Evangelism and Advertising at Coiled, will train you all the things you needed to learn about scaling your information science work to bigger datasets and bigger fashions, whereas staying within the consolation of the PyData ecosystem (numpy, pandas, scikit-learn, Jupyter notebooks). This stay code alongside session is a collaboration between DataCamp and Coiled.

You may come away figuring out:

  • How one can cause about when it’s good to scale your information and machine studying work and when to not;
  • How one can leverage distribute computation in your native workstation (equivalent to you laptop computer) to investigate bigger datasets and construct bigger, extra advanced fashions;
  • How one can harness the ability of clusters to assist larger-than-memory computation, all from the consolation of your individual laptop computer;
  • How one can do all of this whereas writing code just like the numpy, pandas, and/or sckit-learn code you already write.

When

Tuesday, September 15th, 2020, four PM EDT

The place

Dwell on our Fb web page. Register to be reminded!

Directions

Comply with the steps discovered on this Github repository if you happen to want to code together with Hugo! All related supplies will likely be within the repository by the top of the day, Monday, September 14th, so make sure that to test it out once more the morning of the stay coding session.

Stipulations

Not so much. It could assist if you happen to knew:

  • programming fundamentals and the fundamentals of the Python programming language (e.g., variables, for loops);
  • a bit about pandas, numpy, and scikit-learn (though not strictly mandatory);
  • a bit about Jupyter Notebooks;
  • your manner across the terminal/shell.
Nonetheless, Hugo finds that crucial and useful prerequisite is a will to be taught new issues, so when you’ve got this high quality, you may undoubtedly get one thing out of this code-along session.

If you would like to only watch and never code alongside, you may even have a good time, and these notebooks will likely be downloadable afterward.

If you’ll code alongside and use the Anaconda distribution of Python 3 (see beneath), Hugo asks that you simply set up it earlier than the session.

Word: Dwell submissions to Kaggle might occur through the occasion, so if you wish to do this, make sure that to register for an account earlier than the session.

If in case you have any ideas, feedback, or questions, be at liberty to succeed in out to Hugo on Twitter: @hugobowne.



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