![Python
• Uses indentation instead of {} for code blocks and
• Uses : after control statements instead of ; at the end of lines:
opposite of C++, Java, etc.
• Lists can have multiple types
• List1 = [‘HACKBAMA’, 6.11, 2017, “Station”, True]
• “ and ‘ are the same
• Objected oriented: Class structures and inheritance
• Python code can look like MatLab, JavaScript, C++, etc.
Easy to learn – lots of tutorials and examples on the web](https://image.slidesharecdn.com/python-170612063852/85/Python-Applications-4-320.jpg)
Python Applications
- 2. Outline • Brief High-Level Overview of Python • Applications • Anaconda • Running Programs • GUI’s • Numerical Methods • Image Processing • GPU Processing • Machine Learning
- 3. Python • Easy to learn: esp. if you have used MatLab and it’s free • Philosophy: “The Zen of Python” • Beautiful is better than ugly • Explicit is better than implicit • Simple is better than complex • Complex is better than complicated • Readability counts • “Interpreted” script language: pyc files – speed • Huge number of free libraries that you can “import”
- 4. Python • Uses indentation instead of {} for code blocks and • Uses : after control statements instead of ; at the end of lines: opposite of C++, Java, etc. • Lists can have multiple types • List1 = [‘HACKBAMA’, 6.11, 2017, “Station”, True] • “ and ‘ are the same • Objected oriented: Class structures and inheritance • Python code can look like MatLab, JavaScript, C++, etc. Easy to learn – lots of tutorials and examples on the web
- 5. Applications: Anaconda • www.continuum.io Julia-Python-R Command Line or Interactive Python IDE: Spyder 2.7 vs 3.6
- 6. Spyder
- 7. Python Development Tools: Visual Studio: https://www.visualstudio.com/vs/python/
- 9. Applications: Running Programs • import os • import winapi32 • Almost all command line commands can be run – both Windows and Linux commands • Useful for running Monte Carlo simulations
- 11. Applications: GUI’s • Tkinter: tcl-tk interface
- 12. Applications: Numerical Methods • NumPy
- 13. Applications: Numerical Methods • SciPy
- 14. Applications: Numerical Methods • Matplotlib numpy + scipy + matplotlib ≈ Matlab - Simulink
- 15. Applications: Image Processing • OpenCV
- 16. Applications: GPU Processing • Pyopencl
- 17. Applications: GPU Processing • PyCUDA
- 18. Applications: Machine Learning • Theano • Windows-based • Automatically uses GPU • TensorFlow • Linux-based: Google • Automatically uses GPU Both packages are used by higher level machine learning libraries
- 19. Applications: Machine Learning • Sklearn: deep belief network
- 20. Applications: Machine Learning • Lasagna Convolutional neural network
- 21. Applications: Machine Learning • Keras Convolutional neural network
- 22. Summary • Python is an easy language to learn • Anaconda is a useful environment for programming with Python • Python supports GUI development • Numpy, Scipy, and Matplotlib gives you the power of Matlab for free • Python allows access to the GPU for parallel processing • Cutting edge machine learning research can be performed using Python Python is Powerful!!!