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Home > Programming > Python – Complete Python, Django, Data Science and ML Guide [Video]
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Python – Complete Python, Django, Data Science and ML Guide [Video]
Python – Complete Python, Django, Data Science and ML Guide [Video]

Python – Complete Python, Django, Data Science and ML Guide: Dive into Programming, Django, Jupyter, Pygame, and AI Essentials [Video]

By Bogdan Stashchuk
Mex$2,666.99
Video Nov 2023 50 hours 30 minutes 1st Edition
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Product Details

Publication date : Nov 1, 2023
Length 50 hours 30 minutes
Edition : 1st Edition
Language : English
ISBN-13 : 9781835465141
Category :
Programming
Languages :
Python (Beginner) , Python (Beginner)
Concepts :
Programming Language
Tools :
Django (Beginner) , Django (Beginner) , Jupyter (Intermediate) , Jupyter (Intermediate)
Table of content icon View table of contents Download code icon Download Code

Key benefits

  • Dive into over 50 hours of comprehensive Python content
  • Perfect for developers, data scientists, and game creators
  • Build dynamic web applications with Django and games harnessing Pygame

Description

Join us on an immersive Python programming journey, spanning over 50 hours of learning. Whether you're a novice or experienced, this course equips you with vital Python skills for careers and projects. Starting from the basics, grasp Python's core principles and proficiency in real-world functions. As Python's popularity grows, this course readies you for the rising demand for Python developers. You'll practice hand-on examples using Python's interpreter and Visual Studio Code with Code Runner to solidify your skills. With a focus on Data Science and Machine Learning, you'll master essential packages such as NumPy, Pandas, Matplotlib, and Scikit-learn, using the versatile Jupyter Notebook. The course extensively covers Python's fundamental aspects, spanning variables, lists, dictionaries, and venturing into advanced topics like classes, loops, modules, and creating virtual environments. The goal is to provide you with a solid Python foundation. You'll also gain insight into functional and object-oriented Python programming, making you a versatile coder. The course is thoughtfully structured, explaining not just "how" but also "why" we use specific methods and best practices. By course end, you'll harness Python's full potential for web and mobile app development, data science, machine learning, and game creation.

What you will learn

Grasp concepts such as data types, loops, and conditional statements to build a robust coding foundation Understand OOP principles like inheritance, encapsulation, and polymorphism for streamlined code Manipulate files, directories, and efficiently manage external modules through Python Master real-world datasets with NumPy, Pandas, Matplotlib and more Ensure code reliability through Python's error handling and master the nuances of PIP and virtual project isolation

What do you get with a video?

Product feature icon Download this video in MP4 format
Product feature icon Access this title in our online reader with advanced features
Product feature icon DRM FREE - Read whenever, wherever and however you want
Buy Now

Product Details

Publication date : Nov 1, 2023
Length 50 hours 30 minutes
Edition : 1st Edition
Language : English
ISBN-13 : 9781835465141
Category :
Programming
Languages :
Python (Beginner) , Python (Beginner)
Concepts :
Programming Language
Tools :
Django (Beginner) , Django (Beginner) , Jupyter (Intermediate) , Jupyter (Intermediate)

Table of Contents

91 Chapters
1. Introduction to Python Chevron down icon Chevron up icon
Introduction to the Complete Python Guide
Course Overview
Where to Write and Run Python Code
Practice Installing Python
Practice - Using the Python Interactive Interpreter
2. Installing and Using Pycharm IDE Chevron down icon Chevron up icon
Installing PyCharm
Getting Familiar with the PyCharm Interface
3. Basics Concepts in Python Chevron down icon Chevron up icon
Key Concept in Python
Main Data Types in Python
Practice - Working with Main Data Types
4. Introduction to Functions and Built-in Functions in python Chevron down icon Chevron up icon
Built-in Functions
Practice - Defining and Using Functions
Practice - Using the Return Statement in Functions
Practice - Exploring Built-in Functions
Practice - Using the built-in dir() Function
Practice - Gathering User Input with the built-in input() Function
5. Code formatting and PEP8 Chevron down icon Chevron up icon
Code Indentations
Practice - Working with Indentations
Following PEP 8 Guidelines
Enabling Auto-Formatting in PyCharm
6. Comments Chevron down icon Chevron up icon
Comments
Practice - Adding Comments to Your Code
7. Expressions and Instructions Chevron down icon Chevron up icon
Understanding Expressions
Understanding Statements
Practice - Using Expressions
Practice - Using Statements
8. Variables Chevron down icon Chevron up icon
Variables
Practice - Defining and Using Variables
9. Data Types and structures Chevron down icon Chevron up icon
Understanding Dynamic Typing
Types and Data Structures Overview
Variables and Objects
Practice - Using the built-in id() Function
Practice - Exploring Core Data Classes (str, int, bool, list, dict)
Practice - Using the built-in isinstance() Function
10. Strings Chevron down icon Chevron up icon
Strings
Practice - String Manipulation
Practice - String Methods
11. String Concatenation Chevron down icon Chevron up icon
String Concatenation
Practice - Concatenating Strings using the + Operator
Practice - Using f-strings for String Formatting
Practice - Alternative String Formatting Methods
12. Numeric Types Chevron down icon Chevron up icon
Integers
Practice - Integers Manipulation
Float Numbers
Practice - Floating-Point Numbers Manipulation
Working with Complex Numbers
13. Boolean Values Chevron down icon Chevron up icon
Boolean Values
Practice - Working with Boolean Values
Type Conversion
14. Magic Methods Chevron down icon Chevron up icon
Magic Methods
Practice - Utilizing Magic Attributes and Methods
15. Lists Chevron down icon Chevron up icon
Lists
List Methods
Practice - Working with Lists
Copying Lists
Practice - Copying Lists
TASK - Working with Lists
16. Dictionaries Chevron down icon Chevron up icon
Dictionaries
Practice - Manipulating Dictionaries
Practice - Dictionary Methods
Other Operations with Dictionaries
Practice - Using the get() Method for Dictionaries
Practice - Converting Other Types to a Dictionary
TASK - Working with Dictionaries
17. Tuples Chevron down icon Chevron up icon
Tuples
Practice - Tuples Manipulation
18. Sets Chevron down icon Chevron up icon
Sets
Practice - Working with Sets
Understanding Set Theory
Set Methods
Practice - Usage of the Set Methods
Practice - Calculating Symmetric Difference of Sets
TASK - Working with Sets
19. Ranges Chevron down icon Chevron up icon
Ranges
Practice - Range Manipulation
Practice - Range Methods and Attributes
20. Working with Sequences Chevron down icon Chevron up icon
Built-in Functions for Sequences
Built-in zip() Function
Practice - Working with zip Objects
Practice - Converting a zip Object to a Dictionary
Comparison of Different Sequences
21. Modifying Objects in Python Chevron down icon Chevron up icon
Understanding Immutable Objects in Python
Understanding Mutable Objects in Python
Strategies to Prevent Object Mutation
Practice - Creating Deep Copies of Objects
22. Functions Chevron down icon Chevron up icon
Functions
Calling Functions. Arguments vs Parameters
Shortest Function in Python
23. Function Arguments Chevron down icon Chevron up icon
Mutable and Immutable Arguments in Function Calls
Practice - Using Mutable and Immutable Objects as Function Arguments
Practice - Mandatory and Optional Positional Arguments
TASK - Functions Manipulation
Function Arguments
24. Args and kwargs in Functions Chevron down icon Chevron up icon
Practice - Using *args to Gather Positional Arguments into a Tuple
Keyword Arguments
Practice - Working with Keyword Arguments
Practice - Using *kwargs to Merge Keyword Arguments in a Dictionary
TASK - Manipulating Function Arguments
Args and kwargs
Practice - Gathering Positional Arguments into the *args Tuple
Practice - Gathering All Keyword Arguments into the **kwargs Dictionary
25. Default Function Parameters Chevron down icon Chevron up icon
Default Function Parameters
Practice - Using Default Function Parameters
26. Docstrings Chevron down icon Chevron up icon
Docstrings
Practice - Writing and Using Docstrings
Practice - Exploring Docstrings
Practice - Adding Docstrings to Functions
27. Callback Functions Chevron down icon Chevron up icon
Callback Functions
Rules for Working with Functions
28. Global and local Variables Chevron down icon Chevron up icon
Scopes
The Global Keyword
Practice - Global and Local Variables
Practice - Using the Global Keyword
29. Operators Chevron down icon Chevron up icon
Operators
Unary and Binary Operators
Practice - Working with Prefix Unary Operators
TASK - Operators
30. Falsy and Truthy Values Chevron down icon Chevron up icon
Falsy and Truthy Values
Practice - Falsy and Truthy Values
31. Logical and Comparison Operators Chevron down icon Chevron up icon
Logical Operators
Practice - Short-Circuit OR Operator
Practice - Short-Circuit AND Operator
Practice - Combining OR and AND Operators
Practice - Examples with Logical Operators
Practice - Comparison Operators
The del Statement
32. Lambda Functions Chevron down icon Chevron up icon
Lambda Functions
Practice - Returning Lambda Functions from Functions
Practice - Sorting a List using Lambda Functions
Practice - Filtering a List using Lambda Functions
33. Error handling Chevron down icon Chevron up icon
Error Handling
Practice - Using Different Error Classes in the Try and Except
Practice - Using Multiple Error Classes in one Except Block and Parent Exception Class
Practice - Using Else and Finally Blocks
Example - Handling File Not Found Errors
Example - Handling Undefined Variable Errors
Practice - Raising Custom Errors
Practice - Handling Raised Errors using Try and Except
Practice - Specifying Types for Function Parameters
TASK - Proper Error Handling
34. Sequence Unpacking Chevron down icon Chevron up icon
Sequence Unpacking
Practice - Unpacking Tuples
Practice - Unpacking a List of Tuples
Practice - Unpacking Remaining Elements
Practice - Unpacking Selected Elements
Practice - Unpacking a List into Positional Arguments
Practice - Unpacking a Dictionary into Keyword Arguments
Practice - Flexibility in Function Calls
35. Unpacking Dictionary Chevron down icon Chevron up icon
Dictionary Unpacking Operator **:
Practice - Using the Dictionary Unpacking Operator
Practice - Merging Two Dictionaries
36. Conditional Statements Chevron down icon Chevron up icon
Conditional Statements
Practice - Working with Multiple if Statements
The if-else Statement
The if-elif Statement
Practice - Combining if, elif, and else Statements
Practice - Considering the Order of Conditions in if Statements
Practice - Incorporating if Statements into Functions
Practice - Using if and return Statements within Functions
Example - Calculating School Grades using if and return in the Function
TASK - Conditional Statements
37. Ternary Operator Chevron down icon Chevron up icon
Ternary Operator
Practice - Utilizing the Ternary Operator
Example - Calculating Discounts with the Ternary Operator
Example - Data Manipulation using the Ternary Operator
Example - Calculating School Grades using the Ternary Operator
38. For-In loop Chevron down icon Chevron up icon
Loops
For-In Loop
Practice - Iterating through Lists and Tuples using For-In Loops
Practice - Iterating through Dictionaries using For-In Loops
Practice - Iterating through Ranges, Strings, and Sets with For-In Loops
TASKS - Working with For-In Loops
39. While Loop Chevron down icon Chevron up icon
While Loop
Practice - Utilizing the While Loop
Example - Making Selections with the While Loop
Practice - Using break Statements in While and For-In Loops
Practice - Using continue and break Statements in While Loops
TASK - While Loop
40. For-In Expression (Comprehension) Chevron down icon Chevron up icon
For-In Expression
List, Set, and Dictionary Comprehensions
Practice - Using List Comprehension
Practice - Using Dictionary Comprehension
Practice - Utilizing Tuple Comprehension
Practice - Converting Tuples to Lists
Example - Constructing Dictionaries from Sequences
Practice - Short For-In Loops with Conditional Statements
Example - Converting Dictionary to Another Dictionary
TASKS - Short For-In Loops
Example - Chaining For-In Expressions
41. Generators Chevron down icon Chevron up icon
Generators in For-In Expressions
Practice - Generators and Iteration over the Generator
42. Decorator Functions Chevron down icon Chevron up icon
Introduction to Decorator Functions
Example - Verifying User Permissions with Decorator Functions
Example - Logging using Decorator Functions
Example - Validating Arguments with Decorator Functions
43. Classes and Objects Chevron down icon Chevron up icon
Classes and Objects
Practice - Understanding Classes and Class Instances
Practice - Adding Instance Attributes through Dot Notation
Adding Instance Attributes using the ..init.. Method
Practice - Incorporating Own Instance Attributes with the ..init.. Method
44. Instance and Class method Chevron down icon Chevron up icon
Instance vs Class Methods
Practice - Inheriting Methods by the Instances
Static Class Methods
Practice - Utilizing Static Methods in Classes
Class Attributes
Practice - Working with Class Attributes
45. Magic Methods in Classes Chevron down icon Chevron up icon
Magic Methods in Classes
Practice - Utilizing Magic Methods in Classes
46. Classes Extension Chevron down icon Chevron up icon
Inheritance from Other Classes
Practice - Extending Classes
47. Classes in Practice Chevron down icon Chevron up icon
Example - Creating Forum, User, and Post Classes
Example - Creating Instances of the Forum, User, and Post Classes
Example - Methods for Finding Users by Username and Email
Example - Method for Finding All Posts by a Specific User
Example - Retrieving User Posts by Email
Example - Adding Parameter Types
Example - Wrapping up the Forum, Users, and Posts Example
48. Key Principles in Object-Oriented Programming (OOP) Chevron down icon Chevron up icon
Encapsulation in Object-Oriented Programming (OOP)
Inheritance in Object-Oriented Programming (OOP)
Polymorphism in Object-Oriented Programming (OOP)
Abstraction in Object-Oriented Programming (OOP)
49. Modules Chevron down icon Chevron up icon
Modules
Practice - Importing Entire Custom Modules
Practice - Selective Imports from Other Modules
Practice - Importing between Different Modules
Practice - Modules in Subfolders
50. Built-in Modules Chevron down icon Chevron up icon
Built-in Modules
Practice - Importing from Built-in Modules
51. What is __name__ and __main__ Chevron down icon Chevron up icon
Practice - _name_ and _main_
Example - Executing Functions only when Module is run Directly
Practice - Packages in Python
52. JavaScript Object Notation (JSON) Chevron down icon Chevron up icon
JavaScript Object Notation (JSON)
Practice - Converting Python Objects to JSON
Practice - Converting from JSON to Python Objects
Practice - Formatting Dictionaries using JSON
TASKS - JSON
53. Working with Files Chevron down icon Chevron up icon
Working with Files
Working with Files and Directories using the os Module
Removing Files and Directories using the os Module
Summary of Directory and File Operations using the os Module
Working with Files and Directories using the Path Class
Iterating over Directories and Removing Files using the Path Class
Reading and Writing Files
Writing and Reading Files using the built-in open Function
Using the with Statement
Removing Files using unlink
TASK - Files
54. Working with zip archives Chevron down icon Chevron up icon
Built-in zipfile Module and Creating Zip Archives
Reading from the Zip Archive
55. Working with CSV Files Chevron down icon Chevron up icon
Working with CSV Files
Iterating over Each Row in the CSV File
56. Working with Dates and Times Chevron down icon Chevron up icon
Built-in datetime Module
Examples - Using the datetime Class
Examples - Converting Strings to Datetime Objects
Example - Working with the timedelta Class
Built-in time Module
57. Generating Random Sequences and Passwords Chevron down icon Chevron up icon
Built-in random Module
Examples - Utilizing choices and shuffle Methods from the random Module
Built-in secrets Module
Examples - Generating CSRF Tokens, URL-Safe Tokens, and OTP Passwords
Example - Generating Strong Passwords
58. Math Module and Recursive Functions Chevron down icon Chevron up icon
Built-in math Module
Recursive Functions
59. Regular Expressions Chevron down icon Chevron up icon
Built-in re Module for Regular Expressions
Example - Creating Patterns for Matching
Example - Email Validation using Regular Expressions
Example - Substring Replacement using Regular Expressions
Example - Removing Excessive Spaces using Regular Expressions
TASK - Password Verification
60. Sending Emails Chevron down icon Chevron up icon
Running smtp4dev SMTP server in a Docker Container
Sending an Email using SMTP
Formatting an Email using an HTML Template
SMTP Wrap-Up and Removing the Docker smtp4dev Container
61. Working with SQLite Database Chevron down icon Chevron up icon
Creating an SQLite3 Database and Table
Writing Data into the SQLite Table
Reading Data from the SQLite Table
SQLite Summary
62. Other Built-in Modules Chevron down icon Chevron up icon
Built-in array Module
Saving Arrays to Files and Reading Arrays from Files
Accessing Program Arguments using the built-in sys Module
Built-in webbrowser Module
63. Virtual Environments Chevron down icon Chevron up icon
Introduction to PIP - Package Manager for Python
Using a Globally Installed requests Package
Uninstalling Globally Installed Packages using PIP
Creating a Python Virtual Environment
Activation and Deactivation of the Virtual Environment in the Shell
Installing Packages within the Virtual Environment
Saving a List of Installed Packages in a Requirements Text File
Challenges of Package Management using Requirements Files
64. Pipenv for Virtual Environments Management Chevron down icon Chevron up icon
Installing pipenv for Virtual Environments Management
Creating a Virtual Environment using pipenv:
Installing Packages using pipenv:
Updating Packages using pipenv:
Recreating Virtual Environment in the Project Folder using pipenv:
Using venv for Virtual Environments in PyCharm:
Using pipenv for Virtual Environments in PyCharm:
65. Introduction to the Django web framework Chevron down icon Chevron up icon
Introduction to the Django Web Framework and Project Overview
Model View Controller (MVC) Programming Pattern
Understanding How MVC Pattern is Implemented in Django
Creating a New PyCharm Project and Installing Django
66. Creating a Django project Chevron down icon Chevron up icon
Creating a New Django Project
Overview of the manage.py File in Django
Starting and Verifying the Django Server
Overview of Settings in the Django Project
Overview of Default Routing Configuration in Django
67. Creating a Django Application Chevron down icon Chevron up icon
Creating the Shop Application in Django
Explaining the Naming of the Django Project as base
Exploring the Contents of the Shop Application
Creating a View Function
Attaching the View Function to a URL:
Adding Shop Application Routes to the Global Project Routing Configuration
68. Database and Migrations in Django Chevron down icon Chevron up icon
Applying Default Migrations in the Django Project
Creating an Admin User in the Django Project
Creating Course and Category Models
Enabling the Shop Application in the Django Project
Creating and Applying Migrations for the Shop Application
Modifying Database Models
Creating a Category using the Category Model in the Shell
Creating Courses using the Course Model in the Shell
Creating Categories and Courses in the Admin Interface
Modifying How Courses and Categories are Displayed in the Admin Panel
Sending Course Titles to the Client in the Response
69. Creating Templates in Django Chevron down icon Chevron up icon
Creating an HTML Template
Using an HTML Template in the View Function
Populating the HTML Template with Data from the Database
How we Connected Templates, Views, and Models
Adding the Bootstrap CSS Library to the HTML Template
70. Extending Other Templates in Django Chevron down icon Chevron up icon
Creating a Base HTML Template for Reuse in Other Templates
Adding a Navigation Bar in the Base Template
TASK - Making the Title of the Web Page Dynamic:
SOLUTION - Making the Title of the Web Page Dynamic:
71. Creating Multiple routes and View Functions Chevron down icon Chevron up icon
Creating a Route for the Single Course Web Page
Creating a View Function for the Single Course
TASK - Creating an HTML Template for the Single Course
SOLUTION - Creating an HTML Template for the Single Course
Responding with a 404 When Course is Not Found in the Database
72. Routing between Pages in Django Chevron down icon Chevron up icon
Setting Up Routing Between Pages Using Relative or Absolute Paths
Setting Up Routing Based on the Names of the URL Patterns
Considering Application Names in the Routing Setup:
Adding a Link to the All Courses Page
Moving the Templates Folder Out of the Shop Application Folder
Modifying the Model for the Courses
Summary of the Django Shop Application
Installing django-tastypie for the API Django Application
73. Creating an API Django Application Chevron down icon Chevron up icon
Creating an API Django Application
Creating Models for the API Application
Configuring Routing for the API Application
Verifying the API Service
Adding Version for the API
Installing Postman and Sending GET and DELETE Requests
74. Managing Authentication for API Requests Chevron down icon Chevron up icon
Creating an API Key for the User
Enabling Authentication and Authorization for the Model and Using DELETE Method
Disabling Authentication Only for GET Requests
Creating a New Resource Using POST Method
Properly Connecting the Course to the Category in POST Requests Using Hydrate Method
Adding Dehydrate Method to Modify Data Before Sending to Client
Summary for Setting Up GET, POST, and DELETE Requests
75. Django Project Refactoring and Admin Settings Chevron down icon Chevron up icon
Refactoring Routing for the API Application
Setting Up Index Route and Adding Navigation to Navbar
Modifying Administrative Panel
Summary of Django Courses Project
76. Creating Games with Pygame Chevron down icon Chevron up icon
Introduction to Pygame and Creating the Game Window
Modifying Background Color of the Game Surface
Displaying a Rectangle in the Game
TASK - Placing Rectangle in the Middle of the Game Window
SOLUTION - Placing Rectangle in the Middle of the Game Window
Moving Rectangle Using Keyboard Arrows
Stopping Rectangle from Moving Outside of the Surface
77. Creating a Shooter Game with Pygame Chevron down icon Chevron up icon
Final Shooter Game Overview
Loading Images for the Game and Fighter
Displaying Fighter on the Surface
Moving Fighter Left or Right
Making Fighter Movement Continuous
Adding the Ball to the Game
Showing Ball Based on Fighter Position
Moving the Ball After Firing
Adding the Alien to the Game
Moving the Alien Down the Surface
78. Interaction of the Elements in the Pygame Chevron down icon Chevron up icon
Detecting Collision Between Alien and Fighter, Ending the Game
Hitting the Alien with the Ball
Increasing Alien Speed After Each Hit
Adding Hit Counter
Shooter Game Summary
79. Game Refactoring using Classes and OOP Chevron down icon Chevron up icon
Start of Shooter Refactoring and Creating the Fighter Class
Adding Methods in the Fighter Class
Creating an Alien Class
Adding Methods in the Alien Class
Creating a Ball Class
Adding Methods in the Ball Class
Creating a Game Class
Adding Methods in the Game Class
Adding Methods for Drawing Elements and Finalizing Refactoring
Game Refactoring Summary
Running the Game After Refactoring
80. Jupyter Notebook Chevron down icon Chevron up icon
Installing Jupyter Notebook
Editing in Jupyter Notebook
Order of Execution of Cells in Jupyter Notebook
Adding Markdown, Saving, and Loading Jupyter Notebooks
81. Jupyter Lab Chevron down icon Chevron up icon
Installing Jupyter Lab and Editing Notebooks
Exploring Features of Jupyter Lab
Installing External Packages in Jupyter Notebook
82. NumPy - Creating Arrays Chevron down icon Chevron up icon
Introduction to NumPy and Creating One-Dimensional Arrays
Two-Dimensional Arrays in NumPy
Understanding Axes in NumPy
Arithmetic Operations with NumPy Arrays
Concatenating NumPy Arrays
Summary of Basic Operations with NumPy Arrays
83. NumPy – Random Values Chevron down icon Chevron up icon
Filling a NumPy Array with Zeroes, Ones, or Random Floats
Generating Random Elements Using randint and uniform:
Understanding Seed Number
NumPy arange, reshape, and flatten Methods
84. NumPy – Examples Chevron down icon Chevron up icon
NumPy Examples 1 and 2 (One-Dimensional Array):
NumPy Examples 3 and 4 (One-Dimensional Array):
NumPy Example 5 (Two-Dimensional Array):
NumPy Example 6 (Two-Dimensional Array):
NumPy Example 7 (Three-Dimensional Array):
NumPy Summary
85. Pandas – Working with DataFrames and Series Chevron down icon Chevron up icon
Introduction to Pandas and Installation
Creating a DataFrame from a Dictionary
Basic Operations with DataFrame
Describing the DataFrame
Finding Null Values in the DataFrame
Finding Columns with Specific Data Type
Series Data Structure in Pandas
Selecting Part of the DataFrame Using loc and iloc Properties
Filtering Data in the DataFrame
Datetime Type in Pandas
Sorting Data in the DataFrame
Adding and Removing Columns and Concatenating DataFrames
Summary of Pandas DataFrames and Series
86. Pandas – Random Data Working with CSV Chevron down icon Chevron up icon
Generating Random Data for DataFrames
Creating a DataFrame Using Random Data
Saving DataFrames to CSV Files
Creating DataFrames from CSV Files
Writing DataFrames to Excel and JSON Files
87. Pandas – Analysing CSV- Loaded DataFrames Chevron down icon Chevron up icon
Analyzing CSV-Loaded DataFrames
Grouping Data in DataFrames
Displaying Series Data on Plots Using Matplotlib
Summary of Example with Random CSV Data
88. Matplotlib – Creating Charts Chevron down icon Chevron up icon
Examples of Plot and Scatter Diagrams Using Matplotlib
Examples of Matplotlib Subplots
Using DataFrames for Creating Diagrams
Boxplots, Area Plots, and Pie Charts
Example of a Heatmap in Matplotlib
Displaying Real-World Data on Various Charts
89. Scikit – Learn - Machine Learning Chevron down icon Chevron up icon
Introduction to Scikit-Learn and Installation
Loading and Analyzing Sample Data for Model Creation
Handling Null Values in DataFrame
Attempting to Create a Model for Predicting Target Values
Encoding Non-Numeric Values in Input Data
Building and Predicting with Cleaned and Encoded Data
Summary of Model for Predicting Favorite Transport
Visualizing DecisionTreeClassifier Model
Creating Charts for Data from the Built Model
Evaluating Model Accuracy
90. Machine Learning Model for Real Data Chevron down icon Chevron up icon
Loading CSV File with Airline Passenger Satisfaction Data
Analyzing DataFrame with Passenger Satisfaction Data
Filling Null Values with Mean Value
Creating Diagrams for Passenger Data Analysis
Manually Encoding Non-Numeric Values in DataFrame
Encoding Non-Numeric Values Using LabelEncoder
Creating Additional Diagrams After Data Cleaning and Encoding
Filtering DataFrame with Passenger Data
Using DecisionTreeClassifier for Model Creation
Measuring Model Accuracy with DecisionTreeClassifier
Using Other Classifiers for Model Creation
Summary of Airline Passenger Satisfaction Project
91. Making Machine Learning Model More Real Chevron down icon Chevron up icon
Removing Passenger Votes from DataFrame
Saving Trained Model for Future Use
Summary of Realistic Model for Passenger Satisfaction Prediction

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Authors (1)

Profile icon Bogdan Stashchuk
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Bogdan Stashchuk is an experienced instructor (over 20+ years) with a software engineering background. He teaches complex stuff in an easy step-by-step manner. All his courses include practical exercises, which allow the learners to follow him from the start of any course till the end. Learners will perform all tasks the same way he does in his video lectures. There are a lot of challenging assignments, the solutions for which are discussed inside the course. This is the perfect combination that enables you to really learn and retain gained knowledge for a long period of time.
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