Contents PYTHON

Python is an interpreted, object-oriented, high-level programming language with dynamic semantics. Its high-level built in data structures, combined with dynamic typing and dynamic binding, make it very attractive for Rapid Application Development, as well as for use as a scripting or glue language to connect existing components together.

  • Python Overview
  • About Interpreted Languages
  • Advantages/Disadvantages of Python pydoc
  • Starting Python
  • Interpreter PATH
  • Using the Interpreter
  • Running a Python Script
  • Python Scripts on UNIX/Windows
  • Python Editors and IDEs.
  • Using Variables
  • Keywords
  • Strings Different Literals
  • Math Operators and Expressions
  • Writing to the Screen
  • String Formatting
  • Command Line Parameters and Flow Control
  • Built-in Functions
  • Lists
  • Tuples
  • Indexing and Slicing
  • Iterating through a Sequence
  • Functions for all Sequences
  • Using Enumerate()
  • Operators and Keywords for Sequences
  • Dictionaries and Sets
  • The xrange() function
  • List Comprehensions
  • Generator Expressions
  • Functions
  • Function Parameters
  • Global Variables
  • Variable Scope and Returning Values. Sorting
  • Alternate Keys
  • Lambda Functions
  • Sorting Collections of Collections
  • Sorting Dictionaries
  • Sorting Lists in Place
  • Errors and Exception Handling
  • Handling Multiple Exceptions
  • The Standard Exception Hierarchy
  • Using Modules
  • The Import Statement
  • Module Search Path
  • Package Installation Ways
  • The Sys Module
  • Interpreter Information
  • STDIO
  • Launching External Programs
  • Paths Directories and Filenames
  • Walking Directory Trees
  • Math Function
  • Random Numbers
  • Dates and Times
  • Zipped Archives
  • Introduction to Python Classes
  • Defining Classes
  • Initializers
  • Instance Methods
  • Properties
  • Class Methods and DataStatic Methods
  • Private Methods and Inheritance
  • Module Aliases and Regular Expressions.
  • Debugging
  • Dealing with Errors
  • Using Unit Tests
  • Project Skeleton
  • Required Packages
  • Creating the Skeleton
  • Project Directory
  • Final Directory Structure
  • Testing your Setup
  • Using the Skeleton
  • Creating a Database with SQLite 3
  • CRUD Operations
  • Creating a Database Object
  • Introduction to Machine Learning
  • Areas of Implementation of Machine Learning
  • Why Python
  • Project Skeleton
  • Major Classes of Learning Algorithms
  • Supervised vs Unsupervised Learning
  • Learning NumPy
  • Learning Scipy
  • Basic plotting using Matplotlib
  • Machine Learning application
  • Classification Problem
  • Classifying with k-Nearest Neighbours (kNN)
  • Algorithm
  • General Approach to kNN
  • Building the Classifier from Scratch
  • Testing the Classifier
  • Measuring the Performance of the Classifier
  • lustering Problem
  • Introduction to Scikit-Learn
  • Introduction to big data
  • Inbuilt Algorithms for Use
  • What is Hadoop and why it is popular
  • Distributed Computation and Functional Programming
  • Understanding MapReduce Framework Sample
  • Map Reduce Job Run
  • HDFS
  • PIG and HIVE Basics
  • Streaming Feature in Hadoop
  • Map Reduce Job Run using Python
  • Writing a PIG UDF in Python
  • Writing a HIVE UDF in Python
  • Pydoop and MRjob Basics