Data Science at Home

Data Science at Home


30 min with data scientist Sebastian Raschka: A New Podcast Episode

February 01, 2016

In this show I interview Sebastian Raschka, data scientist and author of Python Machine Learning.
In addition to the fun we had offline, there are great elements about machine learning, data science, current and future trends, to keep an ear on. Moreover, it is the conversation of two data scientists who contribute and operate in the field, on a daily basis.

This episode is guaranteed to have great insights.
Enjoy!
Podcast Notes
Why Python?

Blog article: http://sebastianraschka.com/blog/2015/why-python.html

Large-scale virtual screening project (finding a sea lamprey pheromone receptor antagonist)

Poster: http://sebastianraschka.com/pdf/poster/screenlamp_poster_2014_v4.pdf
Recent news about our project (Sea Lamprey Mating Pheromone Registered By U.S. Environmental Protection Agency As First Vertebrate Pheromone Biopesticide): https://t.e2ma.net/message/8ocei/o5r9mj

TPOT - Machine Learning Pipeline Optimization
TPOT GitHub Repo: https://github.com/rhiever/tpot

Semi-Supervised Learning

Singh, Aarti, Robert Nowak, and Xiaojin Zhu. "Unlabeled data: Now it helps, now it doesn't." Advances in neural information processing systems. 2009.
http://papers.nips.cc/paper/3551-unlabeled-data-now-it-helps-now-it-doesnt

Book Recommendations

P.-N. Tan, M. Steinbach, and V. Kumar. Introduction to Data Mining, (First Edition). Addison-Wesley Longman Publishing Co., Inc., Boston, MA, USA, 2005.  http://www-users.cs.umn.edu/~kumar/dmbook/index.php
Sebastian Raschka. Python Machine Learning. Packt Publishing Ltd.
https://github.com/rasbt/python-machine-learning-book
T. Hastie, R. Tibshirani, J. Friedman, T. Hastie, J. Friedman, and R. Tibshirani. The Elements of Statistical Learning, volume 2. Springer, 2009.  http://statweb.stanford.edu/~tibs/ElemStatLearn/
C. M. Bishop et al. Pattern recognition and machine learning, volume 1. springer New York, 2006.
http://www.springer.com/us/book/9780387310732
Duda, Richard O., Peter E. Hart, and David G. Stork. Pattern classification. John Wiley & Sons, 2012.
http://www.wiley.com/WileyCDA/WileyTitle/productCd-0471056693.html
Pedro Domingos. The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World. New York: Basic Books, 2015.
https://homes.cs.washington.edu/~pedrod/