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How to run a Python script On Ubuntu 22.04 LTS / Ubuntu 24.04 LTS Linux 121gamers 0 Mga view • 8 buwan kanina

In this Python Programming Tutorial for Beginners video I am going to show you How to Install Pip packages on Ubuntu 18.04 or How to use Ubuntu 18.04 Linux for installing and managing Pip and PyPI (Python Package Index) Python packages. So What Is PIP for Python? The pip is a command line tool for installing and managing Python packages, which a generally available in the Python Package Index. The official website for Python Package Index (PyPI) is https://pypi.org. PyPI enables us to find and install python related software developed and shared by the Python community. How to Install PIP for Python on Windows, Mac, and Linux ?
So let us see How to Install Python Pip On Ubuntu 18.04?

Give the following command to get the help:
pip --help

Usage:
pip [command] [options]

Commands:
install Install packages.
download Download packages.
uninstall Uninstall packages.
freeze Output installed packages in requirements format.
list List installed packages.
show-Show information about installed packages.
check-Verify installed packages have compatible dependencies.
config - Manage local and global configuration.
search-Search PyPI for packages.
wheel-Build wheels from your requirements.
hash-Compute hashes of package archives.
completion-A helper command used for command completion.
help Show help for commands.

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APPRENDRE PYTHON [TUTO PROGRAMMATION COMPLET DÉBUTANT] 121gamers 0 Mga view • 8 buwan kanina

Vous souhaitez apprendre la programmation de manière simple et efficace ?
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AU PROGRAMME :
-----------------------------
00:00:00 - Introduction
00:01:33 - ETAPE 1 : Installation des logiciels sur votre ordinateur (Windows ou Mac)
00:01:53 - Installation de Python (Python version 3)
00:05:43 - Installation de PyCharm (Environnement de développement)
00:11:48 - Installation de Visual Studio Code
00:15:31 - ETAPE 2 : Les concepts de la programmation (variables, fonctions, boucles...)
00:16:06 - Comment fonctionne la programmation ?
00:24:58 - ETAPE 3 : Création d'un premier programme en Python
00:36:39 - CONSEIL : Les interfaces graphiques (Jeux, applications mobiles iOS/Android, web...)
00:38:02 - Demander des données à l'utilisateur
00:42:05 - EXERCICE : Demander l'age de l'utilisateur
00:44:36 - CONSEIL : Quels types de projets vous voulez faire avec Python ?
00:45:10 - Les commentaires dans le code
00:48:39 - Variable numérique
00:55:34 - Convertir une chaîne en entier
00:57:58 - Erreurs et gestion des exceptions
01:02:42 - CONSEIL : Téléchargez la fiche récap (fichier PDF)
01:03:19 - La boucle "While"
01:10:31 - Améliorer notre programme avec la boucle
01:16:11 - Utiliser le debugger
01:20:24 - CONSEIL : Savoir debugger vous rendra "invincible" en programmation
01:21:34 - EXERCICE : Tester si le nom est vide
01:24:01 - Améliorer notre programme : Fonction
01:30:22 - EXERCICE : Créer une fonction pour demander le nom
01:32:18 - Variable globale et paramètre
01:37:53 - EXERCICE : Créer une fonction pour afficher les informations
01:40:12 - Condition et variable "Booléen"
01:44:10 - Condition "elif"
01:50:00 - EXERCICE : Conditions
01:52:50 - Condition ET / OU
01:55:36 - La boucle "For"
02:00:20 - Nombres à virgules et paramètre optionnel
02:04:04 - Les chaînes formatées
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02:14:20 - Conclusion

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Getting Started with Python in Atom | Python with Atom editor 121gamers 1 Mga view • 8 buwan kanina

Streamlit Python Course: Build a Machine Learning App to Predict Cancer 121gamers 1 Mga view • 8 buwan kanina

Welcome to this Streamlit Python tutorial, where we will dive into creating an interactive machine-learning web application using the Streamlit framework! In this comprehensive project-based course, you'll learn how to build a machine-learning dashboard to predict whether a cell cluster is benign or malignant using Python and Streamlit. This tutorial is perfect for beginners, experienced developers, and data scientists looking to learn how to create powerful machine-learning projects that integrate with web applications.

-----------------------
🔥 Useful links:
- Github project: https://github.com/alejandro-a....o/streamlit-cancer-p
- Blog post: https://alejandro-ao.com/posts..../data-science/stream

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------------------------

🚀 What you'll learn in this tutorial:

How to create a Streamlit dashboard
Training a logistic regression model for machine learning
Visualizing data using Plotly
Displaying predictions based on user input
Creating an AI full-stack app using Python

In this video tutorial, we train a logistic regression model using machine learning in Python. We will be using a dataset to predict whether a cell cluster is benign or malignant. Once our model is ready, we will integrate it into a Streamlit application that runs in the web browser. You'll see how easy it is to create an interactive dashboard using Streamlit and Python!

Next, we will visualize our data using Plotly to create informative and interactive charts. These visualizations will help users understand the predictions made by our machine-learning model. We'll then display the predictions based on the user's input, making our dashboard not only visually appealing but also highly functional.

Throughout the tutorial, we'll explore various techniques and best practices used by experts like Nicholas Renotte and Patrick Loeber. This Streamlit tutorial is an excellent resource for data science dashboard projects and a great way to learn how to create a machine learning app.

By the end of this course, you will have created an AI full-stack app using Python, Streamlit, and machine learning. You'll be ready to tackle your own machine-learning projects and create amazing data science dashboards!

Don't forget to like, comment, and subscribe to stay updated with more tutorials and projects in machine learning, data science, and web app development!

⏰ Timestamps
0:00 Intro
2:56 Download the data
6:23 Project setup
8:21 Clean the data
14:00 Train the model
21:06 Test the model
26:39 Export the model and scaler
32:33 Create the Streamlit app
38:48 Create the layout
44:18 Add the sidebar inputs
58:52 Create the chart
1:17:22 Scale the values for chart
1:25:30 Display the predictions
1:39:08 Add custom CSS
1:52:00 Deploy your app

🎯 Keywords: Streamlit Python, Streamlit Tutorial, Streamlit Dashboard, Machine Learning Python, Machine Learning App Tutorial, Python App, Machine Learning Projects, Machine Learning Projects for Beginners, Nicholas Renotte, Patrick Loeber, AI App, AI Full-Stack App, Data Science Dashboard, Data Science Dashboard Projects

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Introduction to Python IDLE | IDLE Installation and Configuration Tutorial | Edureka 121gamers 4 Mga view • 8 buwan kanina

** Python Certification Training: https://www.edureka.co/python **
This Edureka video on 'Python IDLE' will train you to use IDLE which is an IDE that comes as a default implementation when you install python.
Below are the topics covered in this video:
What is IDLE?
IDLE Installation
Working with IDLE
Configuration
Basic Examples

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2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course.
3. At the end of the training, you will be working on a real-time project for which we will provide you a Grade and a Verifiable Certificate!

- - - - - - - - - - - - - - - - -
About the Course

Edureka's Python Online Certification Training will make you an expert in Python programming. It will also help you learn Python the Big data way with integration of Machine learning, Pig, Hive and Web Scraping through beautiful soup. During our Python Certification training, our instructors will help you:

1. Master the Basic and Advanced Concepts of Python
2. Understand Python Scripts on UNIX/Windows, Python Editors and IDEs
3. Master the Concepts of Sequences and File operations
4. Learn how to use and create functions, sorting different elements, Lambda function, error handling techniques and Regular expressions ans using modules in Python
5. Gain expertise in machine learning using Python and build a Real Life Machine Learning application
6. Understand the supervised and unsupervised learning and concepts of Scikit-Learn
7. Master the concepts of MapReduce in Hadoop
8. Learn to write Complex MapReduce programs
9. Understand what is PIG and HIVE, Streaming feature in Hadoop, MapReduce job running with Python
10. Implementing a PIG UDF in Python, Writing a HIVE UDF in Python, Pydoop and/Or MRjob Basics
11. Master the concepts of Web scraping in Python
12. Work on a Real Life Project on Big Data Analytics using Python and gain Hands on Project Experience

- - - - - - - - - - - - - - - - - - -
Why learn Python?

Programmers love Python because of how fast and easy it is to use. Python cuts development time in half with its simple to read syntax and easy compilation feature. Debugging your programs is a breeze in Python with its built in debugger. Using Python makes Programmers more productive and their programs ultimately better. Python continues to be a favorite option for data scientists who use it for building and using Machine learning applications and other scientific computations.
Python runs on Windows, Linux/Unix, Mac OS and has been ported to Java and .NET virtual machines. Python is free to use, even for the commercial products, because of its OSI-approved open source license.
Python has evolved as the most preferred Language for Data Analytics and the increasing search trends on python also indicates that Python is the next "Big Thing" and a must for Professionals in the Data Analytics domain.

Who should go for python?

Edureka’s Data Science certification course in Python is a good fit for the below professionals:

· Programmers, Developers, Technical Leads, Architects
· Developers aspiring to be a ‘Machine Learning Engineer'
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· Business Analysts who want to understand Machine Learning (ML) Techniques
· Information Architects who want to gain expertise in Predictive Analytics
· 'Python' professionals who want to design automatic predictive models

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