Presentations, code and links to videos for the PyData London Conference 2015 that was held at Bloomberg near Moorgate in London.
| Title | Author(s) | Video | Presentation | Code |
|---|---|---|---|---|
| Accelerating Scientific Code with Numba | Graham Markall | Youtube | Website | |
| Analysis and transformation of geospatial data using Python | Demeter Sztanko | |||
| Getting started with Bokeh / Let's build an interactive data visualization for the web..in Python! | Sarah Bird, Bryan Van de Ven | Youtube | iPython Notebook, Github | iPython Notebook |
| Getting Started with Cloud Foundry for Data Science | Ian Huston | Youtube | SpeakerDeck | Github |
| How “good” is your model, and how can you make it better? | Chih-Chun Chen, Dimitry Foures, Elena Chatzimichali, Giuseppe Vettigli, Raoul-Gabriel Urma | Youtube | iPython Notebook, Github | iPython Notebook, Github |
| Open Source Tools for Financial Time Series Analysis and Visualization | Yves Hilpisch | |||
| Probabilistic programming in sports analytics | Peadar Coyle | |||
| Spark. A View from the Trenches | Sahan Bulathwela, Maria Mestre | Youtube | iPython Notebook, Nbviewer | iPython Notebook, Nbviewer |
| Title | Authors | Video | Presentation | Code |
|---|---|---|---|---|
| A Beginner's Guide to Building Data Pipelines with Luigi | Dylan Barth, Stuart Coleman | |||
| A Fast, Offline Reverse Geocoder in Python | Ajay Thampi | |||
| A practical guide to conquering social network data | Benjamin Chamberlain, Davide Donato, Josh Levy-Kramer | |||
| A Tube Story: How can Python help us understand London's most important transportation network? | Camilla Montonen | |||
| Agent-Based Modelling, the London riots, and Python | Thomas French, Fred Farrell | |||
| Collect and Visualise Metrics With InfluxDB and Grafana | Marek Mroz | |||
| Constructing protein structural features for Machine Learning | Ricardo Corral Corral | |||
| Data-visualisation with Python and Javascript: crafting a data-viz toolchain for the web | Kyran Dale | |||
| Defining Degrees of Separation in Data Classifications Using Predictive Modelling | Yiannis Pavlosoglou, Adam Reviczky, Neri Van Otten | |||
| Deploying a Model to Production | Alex Chamberlain | |||
| Financial Risk Management: Analytics and Aggregation with the PyData stack | Miguel Vaz | |||
| Getting Meaning from Scientific Articles | Éléonore Mayola | |||
| Hacking Human Language | Hendrik Heuer | |||
| Hierarchical Data Clustering in Python | Frank Kelly | |||
| How DataKind UK helped Citizens Advice get more from their data | Emma Prest, Billy Wong | |||
| How We Turned Everyone at Our Company into Analysts with Python and SQL | Arik Fraimovich | |||
| Hyperparameter Optimisation for Machine Learning in Python: Building an automatic scientist | Thomas Greg Corcoran | |||
| If It Weighs the Same as a Duck: Detecting Fraud with Python and Machine Learning | Ryan Wang | |||
| Information Surprise or How to Find Data | Oleksandr Pryymak | |||
| Integration with the Vernacular | James Powell | |||
| Jointly Embedding knowledge from large graph databases with textual data using deep learning | Armando Vieira | |||
| Jupyter (IPython): how a notebook is changing science | Juan Luis Cano | |||
| Keynote - How to Find Stories in Data | Helena Bengtsson | |||
| Keynote - What's it Like to be a Bot? | Eric Drass | |||
| Keynote: CRISP-DM: The Dominant Process for Data Mining | Meta S. Brown | |||
| Localising Organs of the Fetus in MRI Data Using Python | Kevin Keraudren | |||
| Machine Learning with Imbalanced Data Sets | Natalie Hockham | |||
| Making Computations Execute Very Quickly | Russel Winder | |||
| NLP on a Billion Documents: Scalable machine learning with Spark | Martin Goodson | |||
| Our Data, Ourselves | Giles Greenway | |||
| Performance Pandas | Jeff Reback | |||
| Political risk event extraction using Python and Apache Storm | Aeneas Wiener | |||
| PyPy, The Python Scientific Community and C extensions | Romain Guillebert | |||
| Python and scikit-learn based open research SDK for collaborative data management and exchange | Grigori Fursin, Anton Lokhmotov | |||
| Python for Image and Text Understanding: One Model to rule them all! | Roelof Pieters | |||
| Rescuing and Exploring Complex Life Science Data | Paul Agapow | |||
| Ship It! | Ian Ozsvald | |||
| Simulating Quantum Physics in Less Than 20 Lines of Pure Python | Katie Barr | |||
| Smart Cars of Tomorrow: Real-Time Driving Patterns | Ronert Obst | |||
| Sudo Make me a (London) Map | Linda Uruchurtu | |||
| The Dark Art of Search Relevancy | Eddie Bell | |||
| The London Air Quality API | Andrew Grieve | |||
| Using the SALib Library for Conducting Sensitivity Analyses of Models | Will Usher | |||
| Veni, Vidi, Voronoi: Attacking Viruses using spherical Voronoi diagrams in Python | Tyler Reddy |