English | MP4 | AVC 1280×720 | AAC 44KHz 2ch | 470 lectures (50h 27m) | 27.44 GB
Learn the most popular Python programming language including Django, Pygame, Jupyter, Data Science and Machine Learning
Python is the easiest programming language in the world. But at the same time, Python is a powerful tool with which you can solve a huge range of different tasks, from file processing to machine learning, data processing, game creation and web application development .
Thus, having learned Python, you can choose a profession from a wide range of vacancies, or you can use Python to create your own applications and solve your own problems.
This course includes many practical tasks, as well as tasks for self-fulfillment.
Python is an object oriented programming language.
Python is also a language with a huge amount of features, but in order to be able to code in Python, you need to UNDERSTAND the key concepts of Python. And that’s what I’m going to focus on with you in this course.
Before writing code and running examples, you will receive from me explanations and answers to questions WHY and WHY , and only after that HOW to write code.
I will not waste your time and therefore I have created the most effective course structure. All the examples that I will explain and run are written by me before the course, but you will write and run the code yourself.
All video lectures in this course are over 50 hours long , but expect to spend around 500 hours to master all the topics of the course, including self-completion of all practical tasks.
In this course you will learn following key topics:
Foundational Python Programming: Learn the fundamental concepts of Python programming, from data types, functions, and variables to control structures like loops and conditional statements.
Object-Oriented Programming (OOP): Dive into the principles of OOP, understanding classes, objects, inheritance, encapsulation, and polymorphism, and discover how to leverage them for efficient code organization.
File Handling and Modules: Explore file manipulation techniques, from working with directories and files using the os module to using external modules, enabling code reuse, and managing packages with PIP.
Web Development with Django: Get an introduction to web development using Django, covering MVC architecture, URL routing, model creation, and interacting with databases to build dynamic web applications.
API Development: Learn to create RESTful APIs using Django and handle API requests and responses, including authentication, authorization, and versioning.
Game Development with Pygame: Enter the world of game development with Pygame, creating interactive games by working with graphics, animations, and user input.
Data Manipulation with NumPy and Pandas: Discover data analysis and manipulation using NumPy and Pandas, covering array operations, dataframes, and handling real-world data sets.
Error Handling: Understand error handling mechanisms in Python ensuring robust and reliable code.
Package Management and Virtual Environments: Master package management using PIP, create virtual environments to isolate projects, and manage dependencies effectively.
Visualization and Machine Learning: Explore data visualization with Matplotlib, and dip your toes into machine learning concepts with Scikit-Learn, covering model creation, evaluation, and prediction.
Why it’s important: This course provides a comprehensive foundation in Python programming, from basic syntax to advanced topics like OOP, web and game development, data manipulation, and more. Understanding these concepts is crucial for building versatile applications, performing data analysis, and even stepping into machine learning, ensuring you’re equipped for a wide range of programming tasks and projects.
After completing this course, you can safely say that you KNOW Python and CAN use the most popular Python functions.
What you’ll learn
- You will learn the basic principles of Python and learn all the main functions that are used most often in real projects and are in demand the most
- You will practice all the examples that I will show throughout the course using the Python interpreter,
- Visual Studio Code with Code Runner
- You will master all the necessary packages for Data Science and Machine Learning such as NumPy,
- Pandas, Matplotlib and Scikit-learn using Jupyter Notebook
- You will learn the basic functionality of Python, ranging from variables, lists, dictionaries, to classes, loops, modules, and creating virtual environments
- In addition, you will learn how to use functional and object-oriented approaches in Python programming.
Table of Contents
Introduction to Python
1 Introduction to the Complete Python Guide
2 Where to Write and Run Python Code
3 Practice Installing Python
4 Practice Using the Python Interactive Interpreter
Installing and Using PyCharm IDE
5 Installing PyCharm
6 Getting Familiar with the PyCharm Interface
Basic Concepts in Python
8 Key Concept in Python
9 Main Data Types in Python
10 Practice Working with Main Data Types
Introduction to Functions and Builtin Functions in Python
11 Builtin Functions
12 Practice Defining and Using Functions
13 Practice Using the Return Statement in Functions
14 Practice Exploring Builtin Functions
15 Practice Using the builtin dir Function
16 Practice Gathering User Input with the builtin input Function
Code Formatting and PEP8
17 Code Indentations
18 Practice Working with Indentations
19 Following PEP 8 Guidelines
20 Enabling AutoFormatting in PyCharm
Comments
21 Comments
22 Practice Adding Comments to Your Code
Expressions and Instructions
23 Understanding Expressions
24 Understanding Statements
25 Practice Using Expressions
26 Practice Using Statements
Variables
27 Variables
28 Practice Defining and Using Variables
Data Types and Structures
29 Understanding Dynamic Typing
30 Types and Data Structures Overview
31 Variables and Objects
32 Practice Using the builtin id Function
33 Practice Exploring Core Data Classes str int bool list dict
34 Practice Using the builtin isinstance Function
Strings
35 Strings
36 Practice String Manipulation
37 Practice String Methods
String Concatenation
38 String Concatenation
39 Practice Concatenating Strings using the Operator
40 Practice Using fstrings for String Formatting
41 Practice Alternative String Formatting Methods
Numeric Types
42 Integers
43 Practice Integers Manipulation
44 Float Numbers
45 Practice FloatingPoint Numbers Manipulation
46 Working with Complex Numbers
Boolean Type
47 Boolean Values
48 Practice Working with Boolean Values
49 Type Conversion
Magic Methods
50 Magic Methods
51 Practice Utilizing Magic Attributes and Methods
Lists
52 Lists
53 List Methods
54 Practice Working with Lists
55 Copying Lists
56 Practice Copying Lists
57 TASK Working with Lists
Dictionaries
58 Dictionaries
59 Practice Manipulating Dictionaries
60 Practice Dictionary Methods
61 Other Operations with Dictionaries
62 Practice Using the get Method for Dictionaries
63 Practice Converting Other Types to a Dictionary
64 TASK Working with Dictionaries
Tuples
65 Tuples
66 Practice Tuples Manipulation
Sets
67 Sets
68 Practice Working with Sets
69 Understanding Set Theory
70 Set Methods
71 Practice Usage of the Set Methods
72 Practice Calculating Symmetric Difference of Sets
73 TASK Working with Sets
Ranges
74 Ranges
75 Practice Range Manipulation
76 Practice Range Methods and Attributes
Working with Sequences
77 Builtin Functions for Sequences
78 Builtin zip Function
79 Practice Working with zip Objects
80 Practice Converting a zip Object to a Dictionary
81 Comparison of Different Sequences
Modifying Objects in Python
82 Understanding Immutable Objects in Python
83 Understanding Mutable Objects in Python
84 Strategies to Prevent Object Mutation
85 Practice Creating Deep Copies of Objects
Functions
86 Functions
87 Calling Functions Arguments vs Parameters
88 Shortest Function in Python
Function Arguments
89 Mutable and Immutable Arguments in Function Calls
90 Practice Using Mutable and Immutable Objects as Function Arguments
91 Practice Mandatory and Optional Positional Arguments
92 TASK Functions Manipulation
93 Function Arguments
Args and kwargs in Functions
94 Practice Using args to Gather Positional Arguments into a Tuple
95 Keyword Arguments
96 Practice Working with Keyword Arguments
97 Practice Using kwargs to Merge Keyword Arguments in a Dictionary
98 TASK Manipulating Function Arguments
99 Args and kwargs
100 Practice Gathering Positional Arguments into the args Tuple
101 Practice Gathering All Keyword Arguments into the kwargs Dictionary
Default Function Parameters
102 Default Function Parameters
103 Practice Using Default Function Parameters
Docstrings
104 Docstrings
105 Practice Writing and Using Docstrings
106 Practice Exploring Docstrings
107 Practice Adding Docstrings to Functions
Callback Functions
108 Callback Functions
109 Rules for Working with Functions
Global and Local Variables
110 Scopes
111 The Global Keyword
112 Practice Global and Local Variables
113 Practice Using the Global Keyword
Operators
114 Operators
115 Unary and Binary Operators
116 Practice Working with Prefix Unary Operators
117 TASK Operators
Falsy and Truthy Values
118 Falsy and Truthy Values
119 Practice Falsy and Truthy Values
Logical and Comparison Operators
120 Logical Operators
121 Practice ShortCircuit OR Operator
122 Practice ShortCircuit AND Operator
123 Practice Combining OR and AND Operators
124 Practice Examples with Logical Operators
125 Practice Comparison Operators
126 The del Statement
Lambda Functions
127 Lambda Functions
128 Practice Returning Lambda Functions from Functions
129 Practice Sorting a List using Lambda Functions
130 Practice Filtering a List using Lambda Functions
Error Handling
131 Error Handling
132 Practice Using Different Error Classes in the Try and Except
133 Practice Using Multiple Error Classes in one Except Block and Parent Exception
134 Practice Using Else and Finally Blocks
135 Example Handling File Not Found Errors
136 Example Handling Undefined Variable Errors
137 Practice Raising Custom Errors
138 Practice Handling Raised Errors using Try and Except
139 Practice Specifying Types for Function Parameters
140 TASK Proper Error Handling
Sequence Unpacking
141 Sequence Unpacking
142 Practice Unpacking Tuples
143 Practice Unpacking a List of Tuples
144 Practice Unpacking Remaining Elements
145 Practice Unpacking Selected Elements
146 Practice Unpacking a List into Positional Arguments
147 Practice Unpacking a Dictionary into Keyword Arguments
148 Practice Flexibility in Function Calls
Unpacking Dictionaries
149 Dictionary Unpacking Operator
150 Practice Using the Dictionary Unpacking Operator
151 Practice Merging Two Dictionaries
Conditional Statements
152 Conditional Statements
153 Practice Working with Multiple if Statements
154 The ifelse Statement
155 The ifelif Statement
156 Practice Combining if elif and else Statements
157 Practice Considering the Order of Conditions in if Statements
158 Practice Incorporating if Statements into Functions
159 Practice Using if and return Statements within Functions
160 Example Calculating School Grades using if and return in the Function
161 TASK Conditional Statements
Ternary Operator
162 Ternary Operator
163 Practice Utilizing the Ternary Operator
164 Example Calculating Discounts with the Ternary Operator
165 Example Data Manipulation using the Ternary Operator
166 Example Calculating School Grades using the Ternary Operator
ForIn Loop
167 Loops
168 ForIn Loop
169 Practice Iterating through Lists and Tuples using ForIn Loops
170 Practice Iterating through Dictionaries using ForIn Loops
171 Practice Iterating through Ranges Strings and Sets with ForIn Loops
172 TASKS Working with ForIn Loops
While Loop
173 While Loop
174 Practice Utilizing the While Loop
175 Example Making Selections with the While Loop
176 Practice Using break Statements in While and ForIn Loops
177 Practice Using continue and break Statements in While Loops
178 TASK While Loop
ForIn Expression Comprehensions
179 ForIn Expression
180 List Set and Dictionary Comprehensions
181 Practice Using List Comprehension
182 Practice Using Dictionary Comprehension
183 Practice Utilizing Tuple Comprehension
184 Practice Converting Tuples to Lists
185 Example Constructing Dictionaries from Sequences
186 Practice Short ForIn Loops with Conditional Statements
187 Example Converting Dictionary to Another Dictionary
188 TASKS Short ForIn Loops
189 Example Chaining ForIn Expressions
Generators
190 Generators in ForIn Expressions
191 Practice Generators and Iteration over the Generator
Decorator Functions
192 Introduction to Decorator Functions
193 Example Verifying User Permissions with Decorator Functions
194 Example Logging using Decorator Functions
195 Example Validating Arguments with Decorator Functions
Objects and Classes
196 Classes and Objects
197 Practice Understanding Classes and Class Instances
198 Practice Adding Instance Attributes through Dot Notation
199 Adding Instance Attributes using the init Method
200 Practice Incorporating Own Instance Attributes with the init Method
Instance and Class Methods
201 Instance vs Class Methods
202 Practice Inheriting Methods by the Instances
203 Static Class Methods
204 Practice Utilizing Static Methods in Classes
205 Class Attributes
206 Practice Working with Class Attributes
Magic Methods in Classes
207 Magic Methods in Classes
208 Practice Utilizing Magic Methods in Classes
Classes Extension
209 Inheritance from Other Classes
210 Practice Extending Classes
Classes on Practice
211 Example Creating Forum User and Post Classes
212 Example Creating Instances of the Forum User and Post Classes
213 Example Methods for Finding Users by Username and Email
214 Example Method for Finding All Posts by a Specific User
215 Example Retrieving User Posts by Email
216 Example Adding Parameter Types
217 Example Wrapping up the Forum Users and Posts Example
Key Principles in ObjectOriented Programming
218 Encapsulation in ObjectOriented Programming OOP
219 Inheritance in ObjectOriented Programming OOP
220 Polymorphism in ObjectOriented Programming OOP
221 Abstraction in ObjectOriented Programming OOP
Modules
222 Modules
223 Practice Importing Entire Custom Modules
224 Practice Selective Imports from Other Modules
225 Practice Importing between Different Modules
226 Practice Modules in Subfolders
Builtin Modules
227 Builtin Modules
228 Practice Importing from Builtin Modules
What is name and main
229 Practice name and main
230 Example Executing Functions only when Module is run Directly
231 Practice Packages in Python
JavaScript Object Notation JSON
232 JavaScript Object Notation JSON
233 Practice Converting Python Objects to JSON
234 Practice Converting from JSON to Python Objects
235 Practice Formatting Dictionaries using JSON
236 TASKS JSON
Working with Files
237 Working with Files
238 Working with Files and Directories using the os Module
239 Removing Files and Directories using the os Module
240 Summary of Directory and File Operations using the os Module
241 Working with Files and Directories using the Path Class
242 Iterating over Directories and Removing Files using the Path Class
243 Reading and Writing Files
244 Writing and Reading Files using the builtin open Function
245 Using the with Statement
246 Removing Files using unlink
247 TASK Files
Working with Zip Archives
248 Builtin zipfile Module and Creating Zip Archives
249 Reading from the Zip Archive
Working with CSV Files
250 Working with CSV Files
251 Iterating over Each Row in the CSV File
Working with Dates and Times
252 Builtin datetime Module
253 Examples Using the datetime Class
254 Examples Converting Strings to Datetime Objects
255 Example Working with the timedelta Class
256 Builtin time Module
Generating Random Sequences and Passwords
257 Builtin random Module
258 Examples Utilizing choices and shuffle Methods from the random Module
259 Builtin secrets Module
260 Examples Generating CSRF Tokens URLSafe Tokens and OTP Passwords
261 Example Generating Strong Passwords
Math Module and Recursive Functions
262 Builtin math Module
263 Recursive Functions
Regular Expressions
264 Builtin re Module for Regular Expressions
265 Example Creating Patterns for Matching
266 Example Email Validation using Regular Expressions
267 Example Substring Replacement using Regular Expressions
268 Example Removing Excessive Spaces using Regular Expressions
269 TASK Password Verification
Sending Emails
270 Running smtp4dev SMTP server in a Docker Container
271 Sending an Email using SMTP
272 Formatting an Email using an HTML Template
273 SMTP WrapUp and Removing the Docker smtp4dev Container
Working with SQLite Database
274 Creating an SQLite3 Database and Table
275 Writing Data into the SQLite Table
276 Reading Data from the SQLite Table
277 SQLite Summary
Other Builtin Modules
278 Builtin array Module
279 Saving Arrays to Files and Reading Arrays from Files
280 Accessing Program Arguments using the builtin sys Module
281 Builtin webbrowser Module
Virtual Environments
282 Introduction to PIP Package Manager for Python
283 Using a Globally Installed requests Package
284 Uninstalling Globally Installed Packages using PIP
285 Creating a Python Virtual Environment
286 Activation and Deactivation of the Virtual Environment in the Shell
287 Installing Packages within the Virtual Environment
288 Saving a List of Installed Packages in a Requirements Text File
289 Challenges of Package Management using Requirements Files
Pipenv for Virtual Environments Management
290 Installing pipenv for Virtual Environments Management
291 Creating a Virtual Environment using pipenv
292 Installing Packages using pipenv
293 Updating Packages using pipenv
294 Recreating Virtual Environment in the Project Folder using pipenv
295 Using venv for Virtual Environments in PyCharm
296 Using pipenv for Virtual Environments in PyCharm
Introduction to the Django Web Framework
297 Introduction to the Django Web Framework and Project Overview
298 Model View Controller MVC Programming Pattern
299 Understanding How MVC Pattern is Implemented in Django
300 Creating a New PyCharm Project and Installing Django
Creating a Django Project
301 Creating a New Django Project
302 Overview of the managepy File in Django
303 Starting and Verifying the Django Server
304 Overview of Settings in the Django Project
305 Overview of Default Routing Configuration in Django
Creating a Django Application
306 Creating the Shop Application in Django
307 Explaining the Naming of the Django Project as base
308 Exploring the Contents of the Shop Application
309 Creating a View Function
310 Attaching the View Function to a URL
311 Adding Shop Application Routes to the Global Project Routing Configuration
Database and Migrations in Django
312 Applying Default Migrations in the Django Project
313 Creating an Admin User in the Django Project
314 Creating Course and Category Models
315 Enabling the Shop Application in the Django Project
316 Creating and Applying Migrations for the Shop Application
317 Modifying Database Models
318 Creating a Category using the Category Model in the Shell
319 Creating Courses using the Course Model in the Shell
320 Creating Categories and Courses in the Admin Interface
321 Modifying How Courses and Categories are Displayed in the Admin Panel
322 Sending Course Titles to the Client in the Response
Creating Templates in Django
323 Creating an HTML Template
324 Using an HTML Template in the View Function
325 Populating the HTML Template with Data from the Database
326 How we Connected Templates Views and Models
327 Adding the Bootstrap CSS Library to the HTML Template
Extending Other Templates in Django
328 Creating a Base HTML Template for Reuse in Other Templates
329 Adding a Navigation Bar in the Base Template
330 TASK Making the Title of the Web Page Dynamic
331 SOLUTION Making the Title of the Web Page Dynamic
Creating Multiple Routes and View Functions
332 Creating a Route for the Single Course Web Page
333 Creating a View Function for the Single Course
334 TASK Creating an HTML Template for the Single Course
335 SOLUTION Creating an HTML Template for the Single Course
336 Responding with a 404 When Course is Not Found in the Database
Routing Between Pages in Django
337 Setting Up Routing Between Pages Using Relative or Absolute Paths
338 Setting Up Routing Based on the Names of the URL Patterns
339 Considering Application Names in the Routing Setup
340 Adding a Link to the All Courses Page
341 Moving the Templates Folder Out of the Shop Application Folder
342 Modifying the Model for the Courses
343 Summary of the Django Shop Application
344 Installing djangotastypie for the API Django Application
Creating an API Django Application
345 Creating an API Django Application
346 Creating Models for the API Application
347 Configuring Routing for the API Application
348 Verifying the API Service
349 Adding Version for the API
350 Installing Postman and Sending GET and DELETE Requests
Managing Authentication for API Requests
351 Creating an API Key for the User
352 Enabling Authentication and Authorization for the Model and Using DELETE Method
353 Disabling Authentication Only for GET Requests
354 Creating a New Resource Using POST Method
355 Properly Connecting the Course to the Category in POST Requests Using Hydrate Me
356 Adding Dehydrate Method to Modify Data Before Sending to Client
357 Summary for Setting Up GET POST and DELETE Requests
Django Project Refactoring and Admin Settings
358 Refactoring Routing for the API Application
359 Setting Up Index Route and Adding Navigation to Navbar
360 Modifying Administrative Panel
361 Summary of Django Courses Project
Creating Games with Pygame
362 Introduction to Pygame and Creating the Game Window
363 Modifying Background Color of the Game Surface
364 Displaying a Rectangle in the Game
365 TASK Placing Rectangle in the Middle of the Game Window
366 SOLUTION Placing Rectangle in the Middle of the Game Window
367 Moving Rectangle Using Keyboard Arrows
368 Stopping Rectangle from Moving Outside of the Surface
Creating a Shooter Game with Pygame
369 Final Shooter Game Overview
370 Loading Images for the Game and Fighter
371 Displaying Fighter on the Surface
372 Moving Fighter Left or Right
373 Making Fighter Movement Continuous
374 Adding the Ball to the Game
375 Showing Ball Based on Fighter Position
376 Moving the Ball After Firing
377 Adding the Alien to the Game
378 Moving the Alien Down the Surface
Interaction of the Elements in the Pygame
379 Detecting Collision Between Alien and Fighter Ending the Game
380 Hitting the Alien with the Ball
381 Increasing Alien Speed After Each Hit
382 Adding Hit Counter
383 Shooter Game Summary
Game Refactoring using Classes and OOP
384 Start of Shooter Refactoring and Creating the Fighter Class
385 Adding Methods in the Fighter Class
386 Creating an Alien Class
387 Adding Methods in the Alien Class
388 Creating a Ball Class
389 Adding Methods in the Ball Class
390 Creating a Game Class
391 Adding Methods in the Game Class
392 Adding Methods for Drawing Elements and Finalizing Refactoring
393 Game Refactoring Summary
394 Running the Game After Refactoring
Jupyter Notebook
395 Installing Jupyter Notebook
396 Editing in Jupyter Notebook
397 Order of Execution of Cells in Jupyter Notebook
398 Adding Markdown Saving and Loading Jupyter Notebooks
Jupyter Lab
399 Installing Jupyter Lab and Editing Notebooks
400 Exploring Features of Jupyter Lab
401 Installing External Packages in Jupyter Notebook
NumPy Creating Arrays
402 Introduction to NumPy and Creating OneDimensional Arrays
403 TwoDimensional Arrays in NumPy
404 Understanding Axes in NumPy
405 Arithmetic Operations with NumPy Arrays
406 Concatenating NumPy Arrays
407 Summary of Basic Operations with NumPy Arrays
NumPy Random Values
408 Filling a NumPy Array with Zeroes Ones or Random Floats
409 Generating Random Elements Using randint and uniform
410 Understanding Seed Number
411 NumPy arange reshape and flatten Methods
NumPy Examples
412 NumPy Examples 1 and 2 OneDimensional Array
413 NumPy Examples 3 and 4 OneDimensional Array
414 NumPy Example 5 TwoDimensional Array
415 NumPy Example 6 TwoDimensional Array
416 NumPy Example 7 ThreeDimensional Array
417 NumPy Summary
Pandas Working with DataFrames and Series
418 Introduction to Pandas and Installation
419 Creating a DataFrame from a Dictionary
420 Basic Operations with DataFrame
421 Describing the DataFrame
422 Finding Null Values in the DataFrame
423 Finding Columns with Specific Data Type
424 Series Data Structure in Pandas
425 Selecting Part of the DataFrame Using loc and iloc Properties
426 Filtering Data in the DataFrame
427 Datetime Type in Pandas
428 Sorting Data in the DataFrame
429 Adding and Removing Columns and Concatenating DataFrames
430 Summary of Pandas DataFrames and Series
Pandas Random Data and Working with CSV
431 Generating Random Data for DataFrames
432 Creating a DataFrame Using Random Data
433 Saving DataFrames to CSV Files
434 Creating DataFrames from CSV Files
435 Writing DataFrames to Excel and JSON Files
Pandas Analysing CSVLoaded DataFrames
436 Analyzing CSVLoaded DataFrames
437 Grouping Data in DataFrames
438 Displaying Series Data on Plots Using Matplotlib
439 Summary of Example with Random CSV Data
Matplotlib Creating Charts
440 Examples of Plot and Scatter Diagrams Using Matplotlib
441 Examples of Matplotlib Subplots
442 Using DataFrames for Creating Diagrams
443 Boxplots Area Plots and Pie Charts
444 Example of a Heatmap in Matplotlib
445 Displaying RealWorld Data on Various Charts
Scikitlearn Machine Learning
446 Introduction to ScikitLearn and Installation
447 Loading and Analyzing Sample Data for Model Creation
448 Handling Null Values in DataFrame
449 Attempting to Create a Model for Predicting Target Values
450 Encoding NonNumeric Values in Input Data
451 Building and Predicting with Cleaned and Encoded Data
452 Summary of Model for Predicting Favorite Transport
453 Visualizing DecisionTreeClassifier Model
454 Creating Charts for Data from the Built Model
455 Evaluating Model Accuracy
Machine Learning Model for Real Data
456 Loading CSV File with Airline Passenger Satisfaction Data
457 Analyzing DataFrame with Passenger Satisfaction Data
458 Filling Null Values with Mean Value
459 Creating Diagrams for Passenger Data Analysis
460 Manually Encoding NonNumeric Values in DataFrame
461 Encoding NonNumeric Values Using LabelEncoder
462 Creating Additional Diagrams After Data Cleaning and Encoding
463 Filtering DataFrame with Passenger Data
464 Using DecisionTreeClassifier for Model Creation
465 Measuring Model Accuracy with DecisionTreeClassifier
466 Using Other Classifiers for Model Creation
467 Summary of Airline Passenger Satisfaction Project
Making Machine Learning Model More Real
468 Removing Passenger Votes from DataFrame
469 Saving Trained Model for Future Use
470 Summary of Realistic Model for Passenger Satisfaction Prediction
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