PyData Madrid 2016
2016-03-12..2016-03-13
Madrid, Spain
| title | author | length |
|---|---|---|
| A Hitchhiker's Guide to Data Science | Christine Doig | 38m |
Overview of concrete claims and tools: Anaconda ships with conda, conda-forge and Anaconda Cloud and now bundles MKL optimizations (previously paid) for faster… | ||
| Understanding Random Forests | Marc Garcia | 44m |
Starts from CART and implements decision trees with entropy and information gain, then actually ensembles them with bagging and per-tree feature subsampling to… | ||
| Embrace conda packages. | Juan Luis Cano Rodríguez | 37m |
Claim: create relocatable binary packages so users stop compiling. Uses conda-build plus CI like AppVeyor and Travis CI to produce Windows macOS and Linux… | ||
| A primer on recommendation systems. | Manuel Garrido Peña | 37m |
Compares concrete approaches: content filtering (feature vectors from items) versus collaborative filtering (user-behavior features), shows that matrix… | ||
| Python tools for webscraping | Jose Manuel Ortega | 45m |
Shows concrete tools and a working Scrapy project that actually crawls the PyData Madrid site, defines items for title speaker time and description, and pipes… | ||
| The solution of inverse problems | Tomás Gómez Álvarez-Arenas | 37m |
Gradient-descent methods are implemented in Python 2.7 implementation and applied to real datasets: chirps (time and frequency domain), LIGO gravitational-wave… | ||
| Towards a full stack python monitoring+analysis framework | Pablo Manuel García Corzo | 43m |
Claim: build a full‑stack Python monitoring + analytics framework ready for SDN/NFV and IoT, not just dashboards. Uses mqtt for internal transport, Tornado for… | ||
| City attractiveness seen through Twitter | Antònia Tugores | 41m |
Method measures city attractiveness by tracking geolocated tweets as mobility proxies and produces three rankings (city-to-world, world-to-city, city-to-city)… | ||
| Lightning Talks - Saturday session. | 40m | |
A rapid-fire set of demos hits concrete outcomes: a Jupyter tweak that swaps CodeMirror themes and fonts (no Windows support yet); an astrodynamics script that… | ||
| New Computer Trends and How This Affects Us | Francesc Alted | 43m |
Claims that CPU‑level compression plus blocking beats raw I/O by reducing transferred bytes and fitting decompression into CPU latency budgets, with examples… | ||
| The Future of NumPy Indexing. | Jaime Fernández | 40m |
NumPy advanced indexing proves powerful but inconsistent: a lookup-table image example yields 200 times faster execution via fancy indexing, yet… | ||
| Woosh: a fast pure-Python search engine library | Claudia Guirao | 27m |
Whoosh is a pure Python search library used to index ~12,000 product records; initial indexing runs at 10–25s for 2,000 documents producing an index ≈10 MB… | ||
| Python for developing an automated trading platform | Miguel Sánchez de León Peque | 30m |
Claims that Python builds a real‑time automated trading platform end to end and shows a working stack: a multiagent core (OSBrain/OSMarkets) using Pyro for… | ||
| Modelling a text corpus using Deep Boltzmann Machines | Ricardo Pio Monti | 34m |
Builds probabilistic text embeddings from about 10,000 abstracts with a vocabulary of 1,000 using deep Boltzmann machines implemented in Python with numpy… | ||
| Remove before flight: Analysing flight safety data. | Jesús Martos, Alejandro Sáez | 43m |
Uses the NTSB database with Pandas, Scikit‑learn to read and clean records, parse DMS lat/long and geocode city/state via Google to reduce missing locations to… | ||
| An Architecture to Tweet Them All | Jesús Sánchez | 28m |
Claims a production-tested pipeline that ingests Twitter via Spark Streaming (Scala), stores raw JSON in CouchDB, uses Kafka/RabbitMQ for IDs between stages… | ||
| Lightning Talks and Closing Address - Sunday. | 38m | |
Series of demos shows what was built and what works: a volume Python package that embeds leaflet plugins into notebooks and animates geojson time-series on… | ||
| Basic Python Packages for Science | Alejandro Saez Mollejo, Siro Moreno | 01h 38m |
Workshop demonstrates concrete results: runnable Jupyter notebooks load CSVs from the PyData Madrid 2016 repo, use Jupyter Notebook with interactive widgets to… | ||
| Pandas for Beginners | Francisco Correoso | 01h 48m |
PyData Madrid 2016
During the workshop the main features and capabilities of Pandas library will be reviewed.
pandas is an open source, BSD-licensed library… | ||
| Python for Distributed Systems | Guillem Borrell | 01h 34m |
Builds a REST service that generates a Julia set image, measures real times and shows a C extension (called syon here) gives about a 4× speedup, then moves… | ||
| Using Containers for Big Data | Francesc Alted | 01h 38m |
Overview of Python data containers for big data storage and processing, comparing in-memory and on-disk options. Covers basic types (lists, dicts), NumPy… | ||
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