PyVideo.org · PyData Berlin 2016 (original) (raw)
Setting up predictive analytics services with Palladium
ExpAn - A Python library for advanced statistical analysis of A/B tests
Removing Soft Shadows with Hard Data
A full Machine learning pipeline in Scikit-learn vs in scala-Spark: pros and cons
Bayesian Optimization and it's application to Neural Networks
Brand recognition in real-life photos
Building a polyglot Data Science Platform on Big Data systems
Connecting Keywords to Knowledge Base Using Search Keywords and Wikidata
Estimating stock price correlations using Wikipedia
Plumbing in Python: Pipelines for Data Science Applications
Predicting political views from text
PySpark in Practice
Python based predictive analytics with GraphLab Create
Smart Banking - Real Time Driven
Spotting trends and tailoring recommendations: PySpark on Big Data in fashion
Visualizing FragDenStaat.de
Visualizing research data: Challenges of combining different datasources
Zero-Administration Data Pipelines using AWS Simple Workflow
Accelerating Python Analytics by In-Database Processing
BigchainDB : a Scalable Blockchain Database, in Python
Bridging the gap: from Data Science to service
Classifying Search Queries Without User Click Data
Data Integration in the World of Microservices
Dealing with TBytes of Data in Realtime
Designing spaCy: Industrial-strength NLP
Frontera: open source, large scale web crawling framework
Functional Programming in Python
How to Trick a Neural Network
Introduction to Julia for Python Developers
Let's play Space Invaders!
Machine Learning at Scale
One in a billion: finding matching images in very large corpora
Predictive modelling with Python
pypet: A Python Toolkit for Simulations and Numerical Experiments
Python and TouchDesigner for Interactive Experiments
Python Data Ecosystem: Thoughts on Building for the Future
Robot uses toddler-like self exploration for the development of body representations
The "Kwargh!" Problem
Usable A/B testing – A Bayesian approach
Using small data in the client instead of big data in the cloud
What every data scientist should know about data anonymization
