Riley Lambert

Riley Lambert

1575255766

Python Tutorial for Beginners - Learn Python from Scratch with Examples

This Python Tutorial for Beginners will help you learn Python programming language and its core concepts with examples from scratch.

This Python tutorial video helps you to learn the following concepts:

  • 1:55 What is Python?
  • 3:40 Why is Python popular?
  • 4:55 Features of Python
  • 6:50 Where is Python used in the industry?
  • 7:50 Learning Path
  • 9:15 Career Opportunities
  • 10:30 How Netflix use Python?
  • 11:55 How does it use Python?
  • 18:15 Python Developer Salary
  • 18:50 Who is Python Developer?
  • 19:20 Python Developer Job Trends
  • 21:55 How to become a Python Developer?
  • 23:05 Who is a Python developer?
  • 33:50 Job Roles
  • 41:40 Emerging Job Roles
  • 44:30 Road Map
  • 47:05 Python Installation
  • 54:30 How to run a Python program?
  • 58:35 Best IDE for Python
  • 59:35 What is an IDE?
  • 59:50 Features of an IDE
  • 1:00:50 Best IDEs of Python
  • 1:07:40 PyCharm Tutorial
  • 1:07:42 Introduction to PyCharm
  • 1:09:07 Features of PyCharm
  • 1:28:02 Comments in Python
  • 1:28:52 What are Comments?
  • 1:29:47 When to use Python?
  • 1:30:22 How to write comments in Python?
  • 1:32:22 Types of Comments
  • 1:35:57 Docstring Comments
  • 1:39:02 Variables & Data Types
  • 1:39:17 Variable definition & Declaration
  • 1:41:22 Data Types
  • 1:41:42 Numbers
  • 1:43:12 String
  • 1:46:02 List
  • 1:48:12 Dictionary
  • 1:50:12 Tuple
  • 1:51:27 Set
  • 1:53:52 Type Conversion
  • 1:54:42 Python Collections
  • 1:57:12 Specialised Collections Data Types
  • 2:14:57 Arrays
  • 2:15:32 What is an Array?
  • 2:17:27 How to create Arrays in Python?
  • 2:20:52 Accessing Array Elements
  • 2:22:42 Basic Array Operations
  • 2:24:27 Adding elements to an Array
  • 2:27:52 Removing Elements of an Array
  • 2:33:42 Slicing an Array
  • 2:36:12 Looping through an Array
  • 2:39:57 Hash Table and HashMap
  • 2:41:37 Creating Dictionaries
  • 2:44:02 Nested dictionaries
  • 2:46:52 Performing Operations on Hash Table
  • 2:55:32 Operators in Python
  • 3:13:17 Loops in Python
  • 3:13:52 Why to use Python?
  • 3:16:12 What are Loops?
  • 3:18:07 Loops in Python
  • 3:18:17 While Loop
  • 3:26:22 For Loop
  • 3:32:22 Nested Loop
  • 3:48:12 Patterns in Python
  • 4:24:27 File Handling
  • 4:25:07 Why need File Handling
  • 4:27:02 Types of Files
  • 4:28:37 What is File Handling?
  • 4:29:22 Python File Handling System
  • 4:32:52 File Operations for Reading
  • 4:41:27 Python File Write Method
  • 4:47:37 Decorator
  • 4:48:22 Functions in Python
  • 4:54:07 Decorators in Python
  • 5:08:32 Lambda
  • 5:10:17 How to write Anonymous functions?
  • 5:29:02 Map-Reduce Functions
  • 5:29:47 Introduction to map(), filter(), reduce()
  • 5:46:22 What are Generators?
  • 5:47:32 Normal functions vs Generators
  • 5:48:02 Writing Generators in Python
  • 5:52:57 Generators with Loops
  • 5:53:57 Generator Expressions
  • 5:56:22 Use-Cases
  • 6:02:27 OOPS Concepts
  • 6:03:07 Classes & Objects
  • 6:33:47 Inheritance in Python
  • 6:36:52 Types of Inheritance
  • 6:42:47 Python Super Function
  • 6:44:52 Exception Handling
  • 6:54:42 Try & Except block
  • 7:05:52 Python Module
  • 7:07:47 How to create a Module?
  • 7:17:33 Python Modules Search Path
  • 7:24:23 Date & Time
  • 7:24:58 time module
  • 7:38:23 Numpy
  • 7:38:58 What is Numpy?
  • 7:41:43 Numpy vs List
  • 7:49:03 Numpy Operations
  • 8:05:23 Numpy Special Functions
  • 8:09:58 SciPy
  • 8:10:48 What is Python SciPy?
  • 8:12:23 Basic Functions
  • 8:15:48 Special Functions
  • 8:18:53 Integration Functions
  • 8:24:43 Linear Algebra
  • 8:26:48 Interpolation Functions
  • 8:28:18 Pandas
  • 8:29:18 Data life-cycle
  • 8:31:23 What is Pandas?
  • 8:35:33 Pandas Operations
  • 8:54:13 Example
  • 8:59:38 Python for Statistics
  • 9:02:43 Pydoop
  • 9:04:03 Matplotlib
  • 9:04:28 Data Visualization
  • 9:09:13 Matplotlib
  • 9:10:13 Types of Plots
  • 9:30:13 Multiple Plots
  • 9:32:18 Seaborn
  • 9:32:53 Introduction to Seaborn
  • 9:33:33 Seaborn vs Matplotlib
  • 9:34:28 How to install Seaborn?
  • 9:34:48 Installing Dependencies
  • 9:35:33 Python Seaborn Functions
  • 9:44:23 Multi-Plot Grids
  • 9:47:08 Plot Aesthetics
  • 9:50:58 FIFA Use-case
  • 10:15:33 OpenCV Tutorial
  • 10:16:03 What is Computer Vision?
  • 10:16:48 How computer reads an Image?
  • 10:18:53 What is OpenCV?
  • 10:19:58 Basic operations with OpenCV
  • 10:27:33 Face Detection
  • 10:27:38 Face Detection using OpenCV
  • 10:31:53 Capturing Video
  • 10:43:28 Use-case - Motion Detector
  • 10:54:58 Web Development Framework
  • 10:55:23 What are Frameworks in Python?
  • 11:08:34 Python Web Development
  • 11:09:04 Python Web Development Libraries
  • 11:09:24 Python & Django
  • 11:28:19 Web Scraping
  • 11:33:49 Packages used for web Scraping

#Python #webdev

What is GEEK

Buddha Community

Python Tutorial for Beginners - Learn Python from Scratch with Examples
Sival Alethea

Sival Alethea

1624291780

Learn Python - Full Course for Beginners [Tutorial]

This course will give you a full introduction into all of the core concepts in python. Follow along with the videos and you’ll be a python programmer in no time!
⭐️ Contents ⭐
⌨️ (0:00) Introduction
⌨️ (1:45) Installing Python & PyCharm
⌨️ (6:40) Setup & Hello World
⌨️ (10:23) Drawing a Shape
⌨️ (15:06) Variables & Data Types
⌨️ (27:03) Working With Strings
⌨️ (38:18) Working With Numbers
⌨️ (48:26) Getting Input From Users
⌨️ (52:37) Building a Basic Calculator
⌨️ (58:27) Mad Libs Game
⌨️ (1:03:10) Lists
⌨️ (1:10:44) List Functions
⌨️ (1:18:57) Tuples
⌨️ (1:24:15) Functions
⌨️ (1:34:11) Return Statement
⌨️ (1:40:06) If Statements
⌨️ (1:54:07) If Statements & Comparisons
⌨️ (2:00:37) Building a better Calculator
⌨️ (2:07:17) Dictionaries
⌨️ (2:14:13) While Loop
⌨️ (2:20:21) Building a Guessing Game
⌨️ (2:32:44) For Loops
⌨️ (2:41:20) Exponent Function
⌨️ (2:47:13) 2D Lists & Nested Loops
⌨️ (2:52:41) Building a Translator
⌨️ (3:00:18) Comments
⌨️ (3:04:17) Try / Except
⌨️ (3:12:41) Reading Files
⌨️ (3:21:26) Writing to Files
⌨️ (3:28:13) Modules & Pip
⌨️ (3:43:56) Classes & Objects
⌨️ (3:57:37) Building a Multiple Choice Quiz
⌨️ (4:08:28) Object Functions
⌨️ (4:12:37) Inheritance
⌨️ (4:20:43) Python Interpreter
📺 The video in this post was made by freeCodeCamp.org
The origin of the article: https://www.youtube.com/watch?v=rfscVS0vtbw&list=PLWKjhJtqVAblfum5WiQblKPwIbqYXkDoC&index=3

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Thanks for visiting and watching! Please don’t forget to leave a like, comment and share!

#python #learn python #learn python for beginners #learn python - full course for beginners [tutorial] #python programmer #concepts in python

Ray  Patel

Ray Patel

1619510796

Lambda, Map, Filter functions in python

Welcome to my Blog, In this article, we will learn python lambda function, Map function, and filter function.

Lambda function in python: Lambda is a one line anonymous function and lambda takes any number of arguments but can only have one expression and python lambda syntax is

Syntax: x = lambda arguments : expression

Now i will show you some python lambda function examples:

#python #anonymous function python #filter function in python #lambda #lambda python 3 #map python #python filter #python filter lambda #python lambda #python lambda examples #python map

Ray  Patel

Ray Patel

1625843760

Python Packages in SQL Server – Get Started with SQL Server Machine Learning Services

Introduction

When installing Machine Learning Services in SQL Server by default few Python Packages are installed. In this article, we will have a look on how to get those installed python package information.

Python Packages

When we choose Python as Machine Learning Service during installation, the following packages are installed in SQL Server,

  • revoscalepy – This Microsoft Python package is used for remote compute contexts, streaming, parallel execution of rx functions for data import and transformation, modeling, visualization, and analysis.
  • microsoftml – This is another Microsoft Python package which adds machine learning algorithms in Python.
  • Anaconda 4.2 – Anaconda is an opensource Python package

#machine learning #sql server #executing python in sql server #machine learning using python #machine learning with sql server #ml in sql server using python #python in sql server ml #python packages #python packages for machine learning services #sql server machine learning services

Art  Lind

Art Lind

1602968400

Python Tricks Every Developer Should Know

Python is awesome, it’s one of the easiest languages with simple and intuitive syntax but wait, have you ever thought that there might ways to write your python code simpler?

In this tutorial, you’re going to learn a variety of Python tricks that you can use to write your Python code in a more readable and efficient way like a pro.

Let’s get started

Swapping value in Python

Instead of creating a temporary variable to hold the value of the one while swapping, you can do this instead

>>> FirstName = "kalebu"
>>> LastName = "Jordan"
>>> FirstName, LastName = LastName, FirstName 
>>> print(FirstName, LastName)
('Jordan', 'kalebu')

#python #python-programming #python3 #python-tutorials #learn-python #python-tips #python-skills #python-development

Art  Lind

Art Lind

1602666000

How to Remove all Duplicate Files on your Drive via Python

Today you’re going to learn how to use Python programming in a way that can ultimately save a lot of space on your drive by removing all the duplicates.

Intro

In many situations you may find yourself having duplicates files on your disk and but when it comes to tracking and checking them manually it can tedious.

Heres a solution

Instead of tracking throughout your disk to see if there is a duplicate, you can automate the process using coding, by writing a program to recursively track through the disk and remove all the found duplicates and that’s what this article is about.

But How do we do it?

If we were to read the whole file and then compare it to the rest of the files recursively through the given directory it will take a very long time, then how do we do it?

The answer is hashing, with hashing can generate a given string of letters and numbers which act as the identity of a given file and if we find any other file with the same identity we gonna delete it.

There’s a variety of hashing algorithms out there such as

  • md5
  • sha1
  • sha224, sha256, sha384 and sha512

#python-programming #python-tutorials #learn-python #python-project #python3 #python #python-skills #python-tips