PyData 2014: A Week of Python from Machine Learning to Data Visualization
Table of Contents
- PyData 2014 Conference Schedule
- Day 1: Monday, May 19, 2014
- Day 2: Tuesday, May 20, 2014
- Day 3: Wednesday, May 21, 2014
- IPython: a modern vision of interactive computing
- Luigi - Batch Data Processing in Python
- Big Data in Fashion
- Bitdeli - A Platform for Creating Custom Analytics in Your Browser
- How Web APIs and Data-centric Tools Power the Materials Project
- MARS Modeling on the Python Data Stack
- Escape from the Curse of the Cluster and the Headache of Hadoop: Highly reliable, high performance processing of 'Big Data' on a Single Box with Python
- Notes
- TODO Follow-up Actions
PyData 2014 Conference Schedule
Day 1: Monday, May 19, 2014
HDF5 is for Lovers
IPython-parallel
Bayesian Machine Learning & Python – Naïve Bayes
Social Network Analysis
scikit-image
Day 2: Tuesday, May 20, 2014
Learning Python
Intro to Network Science
PyCascading for Intuitive Flow Processing With Hadoop
Practical Time Series Modeling and Analysis
Scaling Machine Learning in Python
Data Visualization With Nodebox
Day 3: Wednesday, May 21, 2014
IPython: a modern vision of interactive computing
Luigi - Batch Data Processing in Python
Big Data in Fashion
Bitdeli - A Platform for Creating Custom Analytics in Your Browser
How Web APIs and Data-centric Tools Power the Materials Project
MARS Modeling on the Python Data Stack
Escape from the Curse of the Cluster and the Headache of Hadoop: Highly reliable, high performance processing of 'Big Data' on a Single Box with Python
Notes
- The conference focused on Python's applications in data science, machine learning, and big data processing.
- Notable talks included advancements in IPython, scikit-learn, and Hadoop integration.
- Emerging trends in fashion analytics and materials science were highlighted.
- The conference emphasized both theoretical concepts and practical applications in Python.
TODO Follow-up Actions
[ ]Review presentation slides when available[ ]Investigate HDF5 for data storage solutions[ ]Explore IPython's latest features for interactive computing[ ]Look into Luigi for potential batch processing projects[ ]Consider implementing Naïve Bayes using Python for upcoming ML tasks