Programming – R & Python

  1. Objectives
    1. Modify scikit-learn for Machine learning
    2. Building and using own web crawler
    3. Linux system administration
  2. Usage
    1. Heavily used by Google
    2. No.2 Used in data science, after R
  3. Contents
    1. Python Basics (https://www.dataquest.io/m/1/python-basics)
      1. Characteristics of Python for Data
        1. handling large datasets
        2. working with common mathematical functions
        3. creating powerful data visualizations
      2. Basic features of programming in Python
        1. Displaying – print():
          1. Numbers: print(4), print(4+5)
  4. References:
    1. Google’s Python Class. https://developers.google.com/edu/python/
    2. Introduction to Python. https://www.udacity.com/course/introduction-to-python–ud1110
    3. Programming Foundations with Python. https://www.udacity.com/course/programming-foundations-with-python–ud036
    4. Learn Python for Data Science. https://www.datacamp.com/courses/intro-to-python-for-data-science?utm_medium=fb%2Can%2Cig%2Cms-all&utm_source=fb_paid&utm_campaign=smartly_ppa&utm_id=5a348450c7e28c19ab425b3b
    5. Top 15 Python Libraries for Data Science in 2017. https://www.kdnuggets.com/2017/06/top-15-python-libraries-data-science.html
    6. 7 Steps to Mastering Data Preparation with Python. https://www.kdnuggets.com/2017/06/7-steps-mastering-data-preparation-python.html
    7. Introduction of Web crawling in Python: http://www-rohan.sdsu.edu/~gawron/python_for_ss/course_core/book_draft/web/web_intro.html
    8. MongoDB and python:
      1. https://realpython.com/blog/python/introduction-to-mongodb-and-python/
      2. http://api.mongodb.com/python/current/tutorial.html
    9. Top 7 Tips for the Model in Android Architectures. https://futurice.com/blog/top-7-tips-for-the-model-in-android-architectures
    10. DataQuest – Pythons Basics. https://www.dataquest.io/m/1/python-basics
      1. login with tabt
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Programming – R & Python

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