Becoming a Data Scientist Podcast Episode 08: Sebastian Raschka

Renee interviews computational biologist, author, data scientist, and Michigan State PhD candidate Sebastian Raschka about how he became a data scientist, his current research, and about his book Python Machine Learning. In the audio interview, Sebastian also joins us to discuss k-fold cross-validation for our model evaluation Data Science Learning Club activity.

Podcast Audio Links:
Link to podcast Episode 8 audio
Podcast’s RSS feed for podcast subscription apps
Podcast on Stitcher
Podcast on iTunes

Podcast Video Playlist:
Youtube playlist of interview videos

More about the Data Science Learning Club:
Data Science Learning Club Welcome Message
Learning Club Activity 8: Evaluation Metrics [coming soon]
Data Science Learning Club Meet & Greet
Now sponsored by DataCamp!

Links to topics mentioned by Sebastian in the interview:

computational biology

molecular docking

Protein-ligand docking

DNA -> RNA -> protein

protein signaling pathways

graph theory

Ensemble learning

cost function

fitness function

ligand and binding affinity

sea lamprey

pheromone

SiteInterlock project

Neural Network

Random Forest

Sebastian’s Python Machine Learning repository on GitHub

Python Machine Learning Book on DataSciGuide

scikit-learnVoting Classifier

softmax regression

stochastic gradient descent

multilayer perceptron

logistic regression (from Sebastian’s github)

regularization in logistic regression (from Sebastian’s github)

Keras deep learning library

@rasbt on Twitter
Sebastian Raschka on Quora


Sebastian’s book on Amazon:



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