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Module 1: Fundamentals of Programming Chapter 2: 2.1 Python for Data Science Introduction Python, Anaconda and relevant packages Link: https://www.youtube.com/watch?v=hbUJ6nd-9lA https://repo.continuum.io/archive/ 2.2 Why learn Python? Python is very simple to pick up; Packages useful for ML are available in Python; Jupyter Notebooks for interactive programming; Extensively used in the industry; Python is much more general purpose programming language; 2.3 Keywords and identifiers Keywords are the reserved words in python; We can’t use a keyword as variable name, function name or any other identifier; Keywords are case sensitive; [Import keyword] Example: False, None, True, class, if, else, return, def, try, while, for, etc Total number of keywords: 33 Identifiers: Name given to entities like class, functions and variables Can be a combination of letters, digits and underscores, cannot start with a digit Keywords cannot be used as identifiers, special characters cannot be used Python has straight forward Error indications; 2.4 Comments, indentations and statements Start a line with a # or use triple quotes, ‘’’ ‘’’ Indentations are used (4 spaces preferred) to make blocks of code, a for loop Rather than writing code in a single line try to write in multiple lines (can use \) to make code readable The written instructions are called statements 2.5 Variables and data types in python Variable is a location in memory used to store some data; Variable d ...
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