Python for Data Analytics and Machine Learning

Role of Python in Data Analytics and Machine Learning

• Learning Objectives
• Data Analysis
• Data Analysis Tools
• Types of Data Analysis
• Phases in a Typical Data Analysis Process
• Introduction to Artificial Intelligence (AI)
• Introduction to Machine Learning
• Types of Machine Learning
• Machine Learning Process
• Some Application Areas of Machine Learning
• Python in Data Analysis and Machine Learning
• Summary
• Practices for 1: Overview

Python and Its Interpreter

• Learning Objectives
• What Is Python?
• Evolution of Python Language
• Applications of Python Programming
• Features of Python
• Comparing Languages
• Python Interpreter Environment – Source Code Encoding
• Invoking the Python Interpreter
• Python Interpreter in Interactive Mode
• Examples of Interactive Mode
• Anaconda and Jupyter Notebook
• Jupyter Notebook – Kernel and Cells
• Jupyter Notebook – Cell Types
• Sample Python Program
• Apache Zeppelin
• Apache Zeppelin Notebook – Creating an Interpreter
• Notebooks in Oracle Machine Learning
• Oracle Machine Learning Notebook – Example
• Creating a Notebook
• Editing a Notebook
• Summary
• Practices for 2: Overview

Python Datatypes

• Learning Objectives
• Python Data Types
• Numbers in Python
• Strings in Python
• Example of String Indexing
• String Operators
• Python String – Example
• List
• Accessing Values in Lists
• List – Example
• Tuples
• Accessing Values in Tuples
• Tuples – Example
• Set
• Accessing a Set in Python
• Dictionaries
• Dictionaries – Example
• Accessing Values in Dictionary
• Summary
• Practices for Lesson 3: Overview

Control Structures in Python

• Learning Objectives
• if statement
• if statement – Example
• else statement
• else statement – Example
• Loop Statements
• for Loop
• for Loop – Example
• Python For-Loop – Range Function
• for Loop – else Statement
• Python while Loop
• while Loop – Example
• while loop – else statement
• Nested Loops
• Loop Control Statements
• Break Statement
• Break Statement – Example
• Continue Statement
• Continue Statement – Example
• Pass Statement
• Summary
• Practices for 4: Overview

Functions in Python

• Learning Objectives
• Functions in Python
• Defining Functions in Python
• Function Invocation
• Pass by Reference
• Function Arguments
• Function Arguments – Required Arguments
• Function Arguments – Default Arguments
• Function Arguments – Keyword Arguments
• Function Arguments – Variable-Length Arguments
• **kwargs
• Scope of Variables
• Lambda Functions with Example
• Using map() function with Lambda Functions
• Recursive Functions
• Summary
• Practices for 5: Overview

Lists in Python

• Learning Objectives
• Sequence Data Types in Python
• Characteristics of Lists in Python
• Accessing Values in Lists
• Negative Indexing in Lists
• Nested Lists in Python
• Slicing a List
• Shallow Copy of a List
• Methods of List Objects
• Examples of List Methods
• List Concatenation: Another Example
• Using a List as a Stack
• Using a List as a Queue
• List Comprehensions
• The del Statement
• Summary
• Practices for 6: Overview

Tuples in Python

• Learning Objectives
• Features of Tuples in Python
• Accessing Values in Tuples
• Negative Indexing in Tuples
• Slicing a Tuple
• Concatenating Tuples
• Immutability of Tuples
• Immutability of Tuples: Deletion of Elements
• Membership Test in Tuples
• Iterating the Elements in a Tuple
• Extending Tuple Elements with *
• Functions Used with Tuples in Python
• Functions Used with Tuples in Python: Example
• Summary
• Practices for 7: Overview

Sets in Python

• Learning Objectives
• Features of Sets in Python
• Accessing a Set in Python
• Updating the Elements in a Set
• Removing the Elements from a Set
• Operations on Sets
• Operations on Sets – Example
• Python Built-in Functions for Sets
• Operations on Sets – Example
• Other Operations on Sets
• Set Comprehension
• Summary
• Practices for 8: Overview

Dictionaries in Python

• Learning Objectives
• Features of Dictionaries
• Accessing Values in Dictionary with Keys
• Updating the Elements in a Dictionary
• Deleting the Elements in a Dictionary
• Properties of Dictionary Keys
• Python Built-in Functions for Dictionary
• Built-in Functions in Dictionary – Example
• Python Built-in Functions for Dictionary
• Operations on Dictionaries – Example
• Dictionary Comprehensions
• Summary
• Practices for 9: Overview

Regular Expressions in Python

• Learning Objectives
• Regular Expression
• Regular Expression: Example
• Metacharacters in Regular Expressions
• Metacharacters in Regular Expression
• Metacharacters in Regular Expressions: Example
• Special Sequences in Regular Expressions
• Special Sequences in Regular Expressions: Examples
• Compiling the Regular Expressions
• Options for Compiling Regular Expressions
• Compiling Regular Expressions: Example
• Summary
• Practices for 10: Overview

Functions of the re Module

• Learning Objectives
• Functions in Regular Expression
• Regular Expression Functions: findall()
• Regular Expression Functions: search()
• Regular Expression Functions: search() – Example
• Regular Expression Functions: split()
• Regular Expression Functions: split() – Example
• Substrings: sub()and subn()
• Regular Expression Functions: match()
• Regular Expression Functions: group()
• Summary
• Practices for 11: Overview

Working with NumPy

• Learning Objectives
• Python Standard Library
• NumPy
• Ndarray Object in NumPy
• Examples of Ndarray Object Creation
• Array Creation
• Array Creation: Example
• Methods to Create Arrays: Example
• Attributes of a NumPy Array
• Attributes of a NumPy Array: Example
• Array Indexing in NumPy
• Array Indexing in NumPy: Example of Slicing
• Array Indexing in NumPy: Integer and Boolean
• Some Arithmetic Operations in Numpy
• Arithmetic Operations in NumPy: Examples
• NumPy: String Functions
• NumPy String Functions: Example
• NumPy String Functions: Example 2
• Descriptive Statistics Using NumPy
• Random Sampling in NumPy
• Sort, Search, and Counting Functions in NumPy
• Sort, Search, and Counting Functions: Example
• Summary
• Practices for 12: Overview

Working with Pandas

• Learning Objectives
• Introduction to Pandas
• Data Structures in Pandas
• Series in Pandas
• Creating a Series: From a NumPy Array
• Creating a Series: From a Dictionary
• Creating a Series: From a List
• DataFrame in Pandas
• Creating a DataFrame: Example
• Adding a New Column to a DataFrame
• Indexing in Dataframes
• DataFrame Indexing: Examples
• join() in Pandas
• join() in Pandas: Example
• Summary
• Practices for 13: Overview

Accessing Data Sources in Python

• Learning Objectives
• Database Access in Python
• Oracle Database Connection in Python
• Oracle Database Connection Using cx_Oracle
• Oracle Database Connection: Example
• Creating a Table Using cx_Oracle
• Insert Operation on Tables Using cx_Oracle
• Update Operation Using cx_Oracle
• Row Delete on Table Data Using cx_Oracle
• Summary
• Practices for 14: Overview

Data Visualization in Python

• Learning Objectives
• Matplotlib
• Matplotlib Functions
• Figure Functions in Matplotlib
• Axis Functions in Matplotlib
• Simple Plot: Example
• Example of Figure: Matplotlib
• Setting Axis Limits and Formatting Axes: Example
• Bar Plot: Matplotlib
• Bar Plot: Matplotlib – Example
• Histogram, Pie Chart, and Scatter in Matplotlib
• Histogram: Example
• Pie Chart: Example
• Scatter Plot: Example
• Seaborn Plotting
• Seaborn Plotting: Example
• Seaborn Plotting Functions
• Seaborn Plotting Functions: Strip Plot
• Seaborn Plotting Functions: Swarm Plot
• Summary
• Practices for 15: Overview