Our Favorite Data, Tech and Science Podcasts

When we're not making Partially Derivative episodes, we spend a lot of time listening to other awesome podcasts about data, technology and science. Add these to your listening lineup for a happier, geekier existence.

Data & Data Science

What's the Point? Big data, small interviews. From FiveThirtyEight.

Data Skeptic Interviews with experts on interesting topics related to data, all through the eye of scientific skepticism.

Linear Digressions Explorations in Machine Learning and Data Science from Udacity.

O'Reilly Data Show Exploring the opportunities and techniques driving big data and data science.

Talking Machines Human conversations about machine learning.

Learning Machines 101 A gentle introduction to artificial intelligence and machine learning.

Programming & Software Engineering

Talk Python to Me Python and related technologies.

podcast.__init__ Python and the people who make it great.

The R Podcast All about the R programming language

Code Newbie Not just for newbies. Great episodes about the craft of programming.

Science

Science Friday News and entertaining stories about science.

Freakonomics The hidden side of everything.

StarTalk Radio A commercial radio program devoted to all things space, hosted by Neil deGrasse Tyson.

Talk Nerdy Interviews with science luminaries by Cara Santa Maria.

Skeptics Guide to the Universe Dedicated to promoting critical thinking, reason, and the public understanding of science through online and other media.

Getting Started with Data Science

Episode 9 was all about getting started with data science. Here's the list of resources we touched on (and some we didn't) in the episode. Data science is a broad field, and learning what you need to know to make it your profession can seem daunting. The most important thing is to dive in, find problems you like to solve, and learn as go. 

• Books
  1. Data Science
     1. Creating a Data Driven Culture
     2. Machine Learning for Hackers
     3. Programming Collective Intelligence
  2. General Data
     1. The Victory Lab
     2. Money Ball
     3. The Signal and the Noise
  3. Programming
     1. Code Complete
     2. The Phoenix Project
     3. Design Patterns
• MOOCs
  1. Andrew Ng's Machine Learning course
  2. Lynda's data science playlist
  3. Intro to data science on Udacity
  4. Thinkful's data science course
     1. Online masters degree courses
        1. UC Berkley
        2. Carnegie Mellon
        3. Northwestern
• Side projects
  1. Kaggle
  2. Email Chris and Jonathon
• Blogs
  1. yhat
  2. David Behnke
  3. Walking Randomly
  4. Hunch
  5. Simply Statistics
  6. FastML
• NBViewer
• Work with an expert
• Stack Overflow
  1. Sites in the Stack Exchange network dedicated to data science
     1. Data Science
     2. Stats
     3. Computer Science
• GitHub
  1. Open Data Science Masters
  2. Hilary Mason
  3. Sean Taylor
• Twitter
  1. Andrew Flowers
  2. DJ Patil
  3. Hilary Mason
  4. Chris Diehl
  5. Sebastian Raschka
  6. Cam Davidson-Pilon
  7. Kirk Borne
  8. Carla Gentry

Programming and Data Science in R

Data scientist and friend of the show Naveen Venkataraman is teaching an R programming workshop at the University of Chicago, and was kind enough to share some fantastic book recommendations -- both from the course and Naveen's professional experience. Check them out!

Programming and Intro books

1. The Art of R Programming - Norman Matloff
2. R for Everyone - Jared Lander 
3. R in Action, Second Edition - Rob Kabacoff
4. The Quick Python Book, Second Edition - Naomi Ceder
5. R Graphics Cookbook (ggplot2) - Winston Chang
6. Advanced R - Hadley Wickham

Modeling

1. Introduction to Statistical Learning (Fourth print) - Hastie, Tibshirani et al
2. Applied Predictive Modeling - Kuhn and Johnson