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29th Meetup

  • AHL

    AHL Riverbank House, 2 Swan Lane, EC4R 3AD, London (map)

    51.509415 -0.088917

  • Note: Please use your full real names where signing up, otherwise we have problems with building security.  

    As always, there'll be free beer and pizza, generously provided by AHL.


    Main speakers:

    Paul Jones on Functional Python

    Although Python is thought of as a procedural and OOP language, there are plenty of features to facilitate the implementation of a functional perspective. Our discussion will encompass the fundamentals of functional programming, whilst demonstrating how we would implement functional techniques in Python. 

    Deenar Toraskar on 10 things you didn't know you could do with interactive notebooks 

    Interactive notebooks were born to address the needs of reproducible research in academia. Spark and the big data stack have given a new lease life to interactive notebook interface. The ability to access distributed storage (HDFS) and having access to a Spark cluster means the notebook is very powerful and able to handle the most complex tasks. This makes it a good choice for a variety of tasks you traditionally didn’t associate with an interactive notebook. 

    Peter Goldsborough on A Tour of Tensorflow

    A walkthrough of a typical Neural Network implementation with Tensorflow, explaining all the moving parts, concepts and differences to similar libraries as we go along.


    Lightning Talks:

    John Stinson on Rich relational data from thin air: how to fake it

    What do you do when you don’t have access to the data you need? Fake it with Python of course! John Stinson will talk about patterns for simulating trends in relational data, based on his recent experience reproducing media-player usage statistics.

    Jose Alberto Esquivel on Embarrassingly parallel data analytics in Python on > 800 cores with AWS Lambda

    If you want to scale up your code to run it on large datasets, don't change it! Keep your beloved DataFrames and Counters. In fact, you can parallelise it on a large number of CPU cores without having to own a large cluster or to rent EC2 nodes. We will show how you can parallelise and run your "big data" experiments in a quick and cost effective way using AWS Lambdas.



    Doors open at 6.30 (get there early as you have to sign-in via AHL's security), talks start at 7pm, beers from 9pm in the bar. We normally have > 200 folk in the room so there's plenty of people to discuss data science questions with!

    Please unRSVP if you realise you can't make it. We're limited by building security on number of attendees, so please free up your place for your fellow community members!

    Follow @pydatalondon for updates and early announcements. See you on the 6th!

Join or login to comment.


    Again within an hour of the meeting I'm on the waiting list. Get a bloody bigger venue guys. Honestly this is not really supporting the community if all of us don't fit.

    5 · November 16

    • Emlyn C.

      True! If people want to congregate in the pub when PyData London is on then that is good idea. We almost always head to The Banker (­), take a pic when you are there, tweet to @pydataldn and we'll retweet that.

      1 · November 17

    • Emlyn C.

      Sorry @pydatalondon, that is.

      November 17

  • Nick D.

    There are hundreds of meet-ups with interesting talks. This one goes so quickly as it is so popular and a built brand.Even if there was a bigger space there would be a waiting list, otherwise they would have to accomodate for 75% of the 5000 members and hey, thats what PyCon is for. So if you are on the waiting list, which includes myself, then just imagine how excited you will be if a place becomes avaliable for you! Thank you to the organisers (volunteers) for putting on such a great and popular meetup. Look forward to the next one I get to attend.

    5 · November 17

  • Darren W.

    This is one of the best Meet Up groups out there. The venue is part of the experience. I unfortunately miss more sessions than I get a place for, but there is generally a good follow up posting of materials for those who can not make it. Keep up the great work PyData team.

    2 · November 16

  • Won Bae S.

    Of course, it goes without saying thank you PyData Organizers for spending your precious time volunteering and hosting such fabulous events every month. We all appreciate your efforts and AHL's sponsorship. Love the cool venue and "wink" food/drinks.

    13 · November 16

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