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Python 101 for Data Science to Absolute Beginners
- 1. 17-Oct-2017!
- 2. Python 101 for Data Science! To Absolute Beginners! @hellocloud_io!
- 3. What to expect :! A lot of new ideas!
- 4. What NOT to expect :! To master or remember everything.!
- 5. Goal :! Foundation for Learning ! Data Science & Python so that ! you can continue learning on your own. !
- 6. The world (human civilization) today is ! traveling faster and faster. !
- 7. 2004! The World is Flat! which is about the world was getting connected. ! Image : www.thomaslfriedman.com !
- 8. 1. The end of the Cold War ( Collapse of the Berlin Wall, Windows PC, Word Processing, Dial- Up Modems )! 2. “viral marketing” – The distribution of Free Software and Services to create a platform for selling other things ( Netscape, Ads on Google Search Result Pages )! 3. Workflow Software ( SMTP, HTML )! 4. The rise of Open Source Software Movement! 5. Outsourcing ( can also be Domestic Outsourcing )! 6. Offshoring ( Assembly of Apple iPhone in China, AMEX Call Center in India, Infosys, Wipro )! 7. Supply-chaining ( e.g : Walmart )! 8. Insourcing ( Japan opens a plant in US and employ Americans to produce Japanese Products ).! 9. Informing ( Google, Yahoo, Wikipedia )! 10. The Steroids ( Wireless, VoIP, Instant Messaging, Mobile )!
- 9. 7 Years Later! Image : www.thomaslfriedman.com !
- 11. Nov, 2016! #1 Age of dizzying Acceleration! #2 Moore’s Law ! #3 The Supernova! A blueprint for how to think about our times.! Image : www.thomaslfriedman.com !
- 12. Image : WEF!
- 13. Image : Visual Capitalist!
- 15. Excerpted From : What The Heck is … Big Data ? – Bernard Marr ! Let’s think about it for a minute !! • When you were reading a book in the past …! • When you were listening to CDs in the past …! • Today, Smart Phones …! • Sensors ( smart ‘x’ ) …! • Internet Searches + Status Updates + Wall Posts + Comments + Likes + Shares … !
- 16. Image : Internet! How Big Data is Used ?! To drive Supermarket Performance! To understand Customers! Transforming Our Family Holidays! Fashion Industry! To crack down on crime and terrorism! To optimize Athletes’ Performance!
- 17. Image : Internet! BIG DATA IN PRACTICE!
- 19. DATA SCIENCE ?!
- 20. Source : HBR!
- 21. Source : Internet! Jeff Hammerbacher! Dr. DJ Patil!
- 28. Read More : http://www2.isye.gatech.edu/~jeffwu/presentations/datascience.pdf!
- 29. Read More : http://courses.csail.mit.edu/18.337/2015/docs/50YearsDataScience.pdf!
- 30. Nobody wants ‘data’.! What they want are the answers.! - Professor David Hand (Imperial College London)!
- 31. Data is only useful! If you can do something with it.!
- 32. Image : Drew Conway’s The Data Science Venn Diagram !
- 36. Image : AWS Big Data Blog!
- 37. Image : AWS Big Data Blog!
- 38. Obtaining Data! 1! Data Science is OSEMN! (pronounced as awesome)! Scrubbing Data! 2! Exploring Data! ! 3! Modeling Data! 4! Interpreting Data ! 5! Reference : Data Science at the Command Line – Jeroen Janssens!
- 39. Different Types of Analytics! Descriptive Analytics! ( What just happened ? )! 1! Diagnostic Analytics! ( Why did it happen ? ) ! 2! Prescriptive Analytics! ( What should I do about it ? )! 3! Predictive Analytics! ( What might happen ? )! 4! Source : talend.com!
- 41. The best way to learn is! To Do!!
- 42. Python!
- 43. • Python Interpreter ( Python 2.7.x or later )! • Numpy! ü Provides a set of array and matrix data types which are essentials for statistics, econometrics and data analysis. ! • Scipy! ü Include a wide range of random number generators, linear algebra routines and optimizers. Scipy depends on Numpy.! • Jupyter Notebook ( Interactive Python Environment )! ü The name Jupyter was inspired by thinking about leading opensource languages for science ( that is, Julia, Python and R )! • matplotlib and seaborn! ü matplotlib provides 2D plots, with limited support for 3D plotting. seaborn improves the default appearance for matplotlib plots without any additional code.! • Pandas! ü Provides high-performance data structures.! • Performance Modules! ü E.g; Cpython and Numba.! Components of Python Scientific Stack!
- 44. Let’s jump into it !!
- 46. Hands-on Lab!
- 47. Q & A!