I’ve just had a fab couple of days at PyConSE in Stockholm, I really enjoyed giving the opening keynote (thanks!) and attending two days of interesting talks. The Saturday was packed with data science talks (see below), it felt like a mini PyData or EuroSciPy, most cool!
The goal of my talk was to show use-cases for why you should do data science, why it is valuable, how to do it successfully with Python and how get the data products deployed. The whole shebang in 40 minutes. Tools mentioned include scikit-learn, statsmodels, textract, pandas, matplotlib, seaborn, bokeh, IPython and Notebooks, Spyder, PyCharm, Flask and Spyre.
Sidenote – this is the follow-on to my “The Real Unsolved Problems in Data Science” opening keynote at PyConIreland 2014.
My main points seemed to make it through, phew!
What I take from @ianozsvald talk:
“How can i turn our data into business value?”
Think + hypothesize + test @pythse
Exploiting your data is key to staying relevant in your business! Listening to @ianozsvald at #pyconse @scalior
Note – I’ll be updating this write-up a little over the next couple of days (it is the end of the conf and I’m rather shattered right now!).
The slides and video for my Data Science Deployed talk are below:
I also plugged PyDataBerlin, our upcoming PyDataLondon (June 19-21, CfP open for just 1 more week) and EuroSciPy on stage, hopefully we’ll see a few more international visitors. I should also have plugged PyConUK too as there’s now a Science Track too!
The following talks from yesterday will interest you, I hope the videos come online soon:
- Analyzing data with Pandas
- Data processing and machine learning with Python (slides)
- Deep Learning and Deep Data Science
- Hacking Human Language
- IPython: How a notebook is changing science
- The Hitchhikers Guide to Python
Here’s a couple of extra links that might be interesting:
- Pandas demo in a Notebook
- Talk on using Bokeh to deploy business apps
- Use Continuum‘s Anaconda to get started – it has all the tools you need
- Software Dev skills for Data Scientists – useful advice
- Dive Into Machine Learning long github list of tutorials and helpful links
Here’s Ilian Iliev’s review of the conference too.
I have a vague idea to write-up these topics more in the future, I’m calling this Building Data Science Products with Python. There’s a mailing list, I’ll email to ask questions a little over the coming months to figure out if/how I should write this.
Thanks everyone for a lovely conference!
Ian applies Data Science as an AI/Data Scientist for companies in ModelInsight and in his Mor Consulting, sign-up for Data Science tutorials in London. He also founded the image and text annotation API Annotate.io, lives in London and is a consumer of fine coffees.