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To be able to have each source{d} book available, we use an Excel sheet to keep track of who has the physical copy. You don't have to request a book if you want to take it to read at home. We just want to make sure to not unnecessarily order the same book twice. "Don't destroy nature unnecessarily!"

source{d} bookshelf take-out (https://docs.google.com/spreadsheets/d/19o9dWwgtluEazZjQQPouLS-C7xubYfYgFgB7qb3QDd4/edit?usp=sharing)

  1. Critical Mass - How one thing leads to another -- Philip Ball
  2. Data Science from Scratch: First Principles with Python -- Joel Grus
  3. DataBase System Concepts -- Abraham Silberschatz
  4. Deep Learning (Adaptive Computation and Machine Learning) -- Goodfellow, Ian
  5. Designing for Growth: A Design Thinking Tool Kit for Managers (Columbia Business School Publishing) -- Liedtka, Jeanne
  6. DevOps for dummies -- Sanjeev Sharma & Bernie Coyne
  7. Effective Python: 59 specific ways to write better Python (Effective software development series) -- Slatkin, Brett
  8. Elasticsearch. THe definitive Guide -- Clinton Gormley & Zachary Tong
  9. Elon Musk (Ecco) -- Vance, Ashlee
  10. Harvard Business Review on Entrepreneurship
  11. Hooked. How To Buid Habit -- Eyal, Nir
  12. Information Dashboard Design: Displaying Data for At-A-Glance Monitoring -- Few, Stephen
  13. Introduction to Information Retrieval Hardback -- Manning
  14. Lean Analytics: Use Data to Build a Better Startup Faster (Lean Series) -- Alistair Croll
  15. Learning IPython for Interactive Computing and Data Visualization - Second Edition -- Rossant, Cyrille
  16. Learning Python -- Mark Lutz
  17. Letters to a Law Student: A Guide to Studying Law at University -- Mcbride, Nicholas J.
  18. Linux System Programming: Talking Directly to the Kernel and C Library -- Robert Love
  19. Mastering Web Application Development with Angular JS -- Pawel Kozlowski & Peter Bacon Darwin.
  20. Mining of Massive Datasets Second Edition -- Leskovec, Jure
  21. Natural Language Processing with Python -- Steven Bird, Ewan Klein & Edward Loper
  22. Nginx HTTP Server - Second Edition -- Clement Nedelcu
  23. Once You’re lucky, twice you’re good -- Sarah Lacy
  24. OpenShift for Developers -- Grant Shipley & Graham Dumpleton
  25. Patrones de diseño -- Erich Gamma
  26. Practical Statistics for Data Scientists: 50 Essential Concepts -- Bruce, Peter
  27. Principles of Marketing -- Philip Kotler & Gary Armstrong
  28. Pro Git -- Chacon, Scott
  29. Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython -- Wes McKinney
  30. Python Machine Learning -- Sebastian Raschka
  31. Python Tricks: A Buffet of Awesome Python Features -- Bader, Dan
  32. Research Design - Second Edition -- John W. Creswell
  33. Sarah’s Key -- Tatiana de Rosnay
  34. Scala for the Impatient -- Horstmann, Cay
  35. Service Virtualization for dummies -- Marcia Kaufman & Judith Hurwitz
  36. Source Code Seeking on the Web: A survey of Empirical Studies and Tools -- Rosalva E. Gallardo-Valencia & Susan Elliot Sim
  37. Take charge product management -- Greg Geracie
  38. Team Geek: A Software Developer's Guide to Working Well with Others -- Brian W. Fitzpatrick
  39. The Definitive ANTLR 4 Reference -- Terence Parr
  40. The Definitive Business Plan -- Richard Stutely
  41. The Lean Startup: How Today's Entrepreneurs Use Continuous Innovation to Create Radically Successful Businesses -- Ries, Eric
  42. The Pocket Universal Principles of Design: 150 Essential Tools for Architects, Artists, Designers, Developers, Engineers, Inventors, and Makers -- Lidwell, William
  43. The Sciences of the Artificial -- Simon, Herbert A.
  44. The starfish and the spider -- Ori Brafman & Rod A. Beckstorm
  45. What we believe but cannot prove -- John Brockman
  46. Who: The A Method for Hiring -- Smart, Geoff
  47. Wikinomics - How mass collaboration changes everything -- Don Tapscott & Anthony D. Williams
  48. Writing An Interpreter In Go -- Ball, Thorsten
  49. Writing Idiomatic Python 3.3 -- Jeff Knupp
  50. Your Code as a Crime Scene: Use Forensic Techniques to Arrest Defects, Bottlenecks, and Bad Design in Your Programs (The Pragmatic Programmers) -- Adam Tornhill