In this video I show how to setup a Raspberry Pi web server and how to connect it to your own domain name (.com, .org, etc.). We start be installing Raspbian, then install software updates, and then install Apache, PHP and MySQL. After verifying that the web server is functioning properly, I show how to sign up for a domain name with Google Domains, and how to use their Dynamic DNS service so your domain will work with typical residential internet service providers. We also install TeraTerm and Swish SFTP on the Windows PC in order to interact with the Raspberry Pi over the network.

This video is similar to an earlier video I made around half a year ago, but this new video covers how to setup a domain name and the Dynamic DNS service.

I have a text summary of this video on my web site, so you don't have to try reading the text off of the video:
http://www.farrellf.com/projec....ts/software/2016-05-

Because no one is going to stoop as low to use HyperV, we're going to be using the Kernel Virtual Machine (KVM) to simulate our operating systems. Now you too can have your own farm of Linux distros and Windows builds you'll never use.

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Chapters:
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4:23 Creating a Virtual Machine
12:42 Running a Virtual Machine
16:44 Spice-vdagent
22:28 Snapshots

As a precursor to getting to more Power Supply and other electronic projects on the go, I want to look at a few programming languages / environments I have not used before

In this case I will look at using Node-Red.

To quote the site http://nodered.org/
"Node-RED
A visual tool for wiring the Internet of Things.
Node-RED is a tool for wiring together hardware devices, APIs and online services in new and interesting ways."

This is a programming environment driven by a graphical WEB page and uses Drag and Drop with configuration of nodes to build your application
Many nodes are available and if you cannot find what you need, it seems to be fairly simple to add you own, and if you know Java then even better.

It will run on many platforms including Windows, Linux and OSX and or course a range of hardware including the PC or Raspberry PI.

A long-time friend of mine "Peter Scargill" has been using Node-RED for a while and provided me access to a few scripts he uses to make configuring the PI a little easier. The process will still take an hour or two but this is including everything from creating a boot SD card through to a full working environment including a Database, MQTT, WEB Admin Pages and many node-RED nodes installed

Pete’s technical blog is here: - http://tech.scargill.net/
His scripts can be found here: - https://bitbucket.org/snippets/scargill/

Node-RED documentation can be found here: - http://nodered.org/
And if you google "Node-Red Nodes" you will find plenty more. Add "Scargill" to the search for many posts by Pete. (He goes by Pete, I go by Peter :) )

And some useful info for node-RED from IBM can be found here: - http://www.techrepublic.com/article/node-red/

I will be following this post with actual programming tutorials and sessions using node-RED very soon so keep an eye out.

Hello and welcome to the second video of this series which explains how to setup your Virtual machine optimized for deep learning on the Google cloud platform.
In this video you will find out the best practices on how to setup your deep learning environment on the google cloud platform.

Feel free to leave us questions and suggestions in the comment sections below.

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🚨🚨📢📢 NEW AI Drone Programming Course 🚨🚨📢📢
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This is the Drone programming with python course. Here we are going to learn the basics of a drone including the components and how the drone flies. Then we will look at the installations and the basic movements along with image capture. From there we will create exciting projects including Surveillance drones, Face tracking, and line following drones.
If you are a beginner don't worry this course is for you we will focus on the implementation part so that you can get the most practical experience out of this. And even though we will be using a specific drone for this course 80% of the material covered in this course can be used with any drone.

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Time Stamps:
00:00 Intro
1:00 What is a drone?
2:14 Components of a drone
05:56 How does a drone fly?
08:42 Tello Drone
11:25 App Setup and Test Run
15:07 Installations
19:21 Basic Movements
31:16 Image Capture
36:27 Keyboard Control
59:13 Project 1 - Surveillance
1:10:34 Project 2 - Mapping
1:52:15 Project 3 - Face Tracking
2:32:18 Project 4 - Line Follower

Stay tuned for more content as we continue our journey through the Backend Dev! 🚀 and make sure to explore the upcoming courses at https://sheryians.com/

Instructor in this video: Ankur Prajapati

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#sheryianscodingschool #sheryians #reactjs #mernstack #mern #web #reactjscourse #tutorial #creativewebdevelopment #webdevelopment #functionalwebdevelopment #thebasics #mernstack #jslogic #javascriptlogics

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

Complete Python Programming Roadmap | How to Become a Python Developer - 9 LPA 🤑

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--------------------------------------| Thanks |---------------------------
#python #pythonprogramming #pythondeveloper

In this video, we are going see how we can practice coding on a cheap and old android tablet. We can compile and run programs in various programming languages such as java or c++ or python. This is useful when you want to practice coding on the go and don't want to carry heavy laptops all the time.

Part 2: https://youtu.be/pw1rtvXEza8

(* Press i to go into editing (insert) mode)

Suggestions are always welcomed. Please mention your queries / issues / doubts in the comments. I'll make sure to answer them.

Thanks for watching. If you really liked the video, please consider subscribing and / or buying me a coffee at: https://www.buymeacoffee.com/binarysource.

This course will give you a full introduction into all of the core concepts related to blockchain, smart contracts, Solidity, ERC20s, full-stack Web3 dapps, decentralized finance (DeFi), JavaScript, TypeScript, Chainlink, Ethereum, upgradable smart contracts, DAOs, the graph, moralis, aave, IPFS, and more. Follow along with the videos and you'll be a blockchain wizard in no time!

💻 Code, resources, and support forum: https://github.com/smartcontra....ctkit/full-blockchai
Please reference the repo for anything you need and feel free to leave issues and participate in the discussions.

⭐️ Course Contents ⭐
⌨️ (00:00:00) Lesson 0: Welcome To Blockchain
⌨️ (00:09:05) Lesson 1: Blockchain Basics
⌨️ (02:01:16) Lesson 2: Welcome to Remix! Simple Storage
⌨️ (03:05:34) Lesson 3: Remix Storage Factory
⌨️ (03:31:55) Lesson 4: Remix Fund Me
⌨️ (05:30:42) Lesson 5: Ethers.js Simple Storage
⌨️ (08:20:17) Lesson 6: Hardhat Simple Storage
⌨️ (10:00:48) Lesson 7: Hardhat Fund Me
⌨️ (12:32:57) Lesson 8: HTML / Javascript Fund Me (Full Stack / Front End)
⌨️ (13:41:02) Lesson 9: Hardhat Smart Contract Lottery
⌨️ (16:34:07) Lesson 10: NextJS Smart Contract Lottery (Full Stack / Front End)
⌨️ (18:51:36) Lesson 11: Hardhat Starter Kit
⌨️ (18:59:24) Lesson 12: Hardhat ERC20s
⌨️ (19:16:13) Lesson 13: Hardhat DeFi & Aave
⌨️ (20:28:51) Lesson 14: Hardhat NFTs
⌨️ (23:37:03) Lesson 15: NextJS NFT Marketplace (Full Stack / Front End)
⌨️ (28:53:11) Lesson 16: Hardhat Upgrades
⌨️ (29:45:24) Lesson 17: Hardhat DAOs
⌨️ (31:28:32) Lesson 18: Security & Auditing

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How to Learn Python Programming Language From Basic? – [Hindi] – Quick Support. क्या आपको प्रोग्रामिंग पसंद है? क्या आप इस फील्ड में बिगिनर हैं और अपना करियर.. प्रोग्रामिंग के कॉम्पिटिटिव वर्ल्ड में स्टार्ट करना चाहते हैं? और क्या एक बिगिनर के तौर पर आप पाइथन लर्निंग के लिए रिसोर्सेस ढूँढ़ रहे हैं? अगर हाँ, तो आज का ये वीडियो आपके लिए है क्योंकि इस वीडियो में हम आपको बताएंगे कि आप कैसे पाइथन प्रोग्रामिंग लैंग्वेज को स्टेप बाय स्टेप सीख सकते हैं, वो भी एकदम बेसिक्स से एडवांस्ड लेवल तक। इसीलिए इस विडियो को पूरा जरुर देखे |

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python snake game code tutorial example explained

We're using Tkinter, because I have not taught PyGame at this point in time, in case you're wondering

#python #snake #game

music credits 🎼 :
===========================================================
Up In My Jam (All Of A Sudden) by - Kubbi https://soundcloud.com/kubbi
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Free Download / Stream: http://bit.ly/2JnDfCE
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===========================================================
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===========================================================

Tkinter is the de facto way in Python to create Graphical User interfaces (GUIs) and is included in all standard Python Distributions. In fact, it's the only framework built into the Python standard library.

Code - https://github.com/campusx-off....icial/python-gui-tki

Wallpaper Viewer App using Tkinter - https://youtu.be/vjh0Cqudqa0
Calculator App - https://youtu.be/owbU6WzIhhg

============================
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👍If you find this video helpful, consider giving it a thumbs up and subscribing for more educational videos on data science!

💭Share your thoughts, experiences, or questions in the comments below. I love hearing from you!

In this video, we're going to discuss how to create a Stock Trend Prediction Web Application in Python. Here we will use Streamlit, an open-source Python library, that makes it easy to build beautiful custom web apps for Machine Learning and Data Science.

Get Python Tutorials For Free [https://www.geeksforgeeks.org/....python-programming-l

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Welcome to part 3 of the web development with Django and Python tutorial series. In this tutorial, we're goign to be checking out the admin functionality that comes with Django.

Text-based tutorial: https://pythonprogramming.net/....admin-apps-django-tu

Channel membership: https://www.youtube.com/channe....l/UCfzlCWGWYyIQ0aLC5
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#django #web-development #python

In this video you will learn to create a Langchain App to chat with multiple PDF files using the ChatGPT API and Huggingface Language Models.

Welcome to our comprehensive step-by-step tutorial on building a powerful chatbot that allows you to ask questions about your multiple PDFs using LangChain and ChatGPT API. In this project-based video tutorial, we will guide you through the process of harnessing the capabilities of LangChain, a cutting-edge framework for developing language model-powered applications.

-----------------------
USEFUL LINKS
👉 Github repo: https://github.com/alejandro-ao/ask-multiple-pdfs

💬 Join the Discord Help Server - https://link.alejandro-ao.com/HrFKZn
❤️ Buy me a coffee... or a beer (thanks): https://link.alejandro-ao.com/l83gNq
✉️ Join the mail list: https://link.alejandro-ao.com/AIIguB
--------------------------

Powered by ChatGPT, an advanced AI language model, our chatbot implementation enables you to interact with your PDF documents in a whole new way. We will also explore the utilization of Huggingface language models to enhance the chatbot's performance.

Throughout this Python tutorial, you'll learn how to integrate LangChain into your application, leveraging its data-awareness and agentic features, allowing your language model to tap into various data sources and interact with its environment seamlessly.

Key Topics Covered:
- Introduction to LangChain and its principles of data awareness and agency
- Exploring the capabilities of ChatGPT API and its potential for artificial intelligence applications
- Step-by-step walkthrough on setting up the LangChain framework in Python
- Integration of Huggingface language models for enhanced chatbot functionality
- Building a project-based chatbot application that answers questions based on your PDFs
- Optimizing your chatbot for efficient and accurate responses
- Best practices for leveraging open-source GPT models, including GPT-3.5 and GPT-4
- Unlocking the potential of ChatGPT and LangChain to create innovative applications

Whether you're a developer, AI enthusiast, or simply curious about the world of artificial intelligence, this tutorial is perfect for you. Join us on this exciting journey to develop your very own PDF-powered chatbot using LangChain, ChatGPT API, and the power of Python.

------------------------------------------------------------------------------
TIMESTAMPS
0:00 Intro
1:31 Setup
3:26 Create GUI
8:50 Add your API Keys
11:46 How this works (Diagram)
16:41 Handle process button
19:43 Extract text from PDFs
24:33 Split text into Chunks
29:26 Embedings
32:30 OpenAI Embeddings
36:24 Instructor Embeddings
40:57 Create ConversationChain
46:18 Make conversation persistent
50:14 HTML templates
55:04 Display Chat History
1:02:05 Free Huggingface LLM
1:06:10 Conclusion

Keywords:
#ChatGPT #streamlit #langchain #OpenAI

This tutorial demonstrates how to build and deploy an android app to your smartphone. The app was programmed with python and the kivy framework. Buildozer, the android debug bridge and the ubuntu subsystem were used to build, deploy and debug the android app. This tutorial works also perfectly fine for Ubuntu.

If anything is unclear, feel free to ask and write a comment.


▬ Links ► ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬

Code of this tutorial:
https://github.com/denczo/kivy_examples
ADB for Windows:
https://dl.google.com/android/....repository/platform-

▬ Commands ► ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬

► Download project
git clone https://github.com/denczo/kivy_examples

► Install buildozer:
git clone https://github.com/kivy/buildozer.git
cd buildozer
sudo python3 setup.py install

► Required libraries and tools:
sudo apt-get update
sudo apt-get install openjdk-8-jdk
sudo apt-get install unzip
sudo apt install python3 python3-pip ipython3
sudo apt install cython
sudo apt-get install autoconf
sudo apt install build-essential libltdl-dev libffi-dev libssl-dev python-dev
sudo pip3 install --upgrade cython
sudo apt-get install zip

► Build & Deployment
buildozer android debug deploy run logcat
adb -s DEVICE_ID logcat *:S python:D
adb -s DEVICE_ID install name.apk

► Connection to phone
adb devices
cmd:
adb tcpip 5555
wsl2 (ubuntu subsystem):
adb connect YOUR_IP:5555


▬ Chapters ► ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬

► 0:00 - Intro
► 0:27 - Install Ubuntu Subsystem
► 2:00 - Install Buildozer
► 4:44 - Buildozer Configuration (Buildozer.spec)
► 10:44 - Build .apk with Buildozer
► 13:50 - Connect Android Phone to PC
► 18:25 - Deploy .apk to Android Phone
► 19:27 - Debug App on Android Phone via terminal
► 21:50 - Outro

▬ Programming ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬

► Pycharm Community Edition
► Python 3.8.1
► Kivy 2.0

▬ Editing ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬

► Sony Vegas Pro Edit 14
► OBS
► t.bone SC400
► Cheap Webcam

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

💬 Join the Discord Help Server - https://link.alejandro-ao.com/HrFKZn
❤️ Buy me a coffee... or a beer (thanks): https://link.alejandro-ao.com/l83gNq
✉️ Join the mail list: https://link.alejandro-ao.com/AIIguB
------------------------

🚀 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!

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⏰ 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

#python #streamlit #MachineLearning #DataScience

Welcome back to another video. In this one I am going over how I scored a Mini PC for use as an at home server on the cheap for running services like Jellyfin, Nextcloud, and more!

Containers mentioned:
Jellyfin: https://hub.docker.com/r/linuxserver/jellyfin
Nextcloud: https://hub.docker.com/_/nextcloud
Time Machine: https://hub.docker.com/r/mbentley/timemachine

Docker Linux Install Instructions: https://docs.docker.com/engine/install/ubuntu/

Song: JPB - Top Floor [NCS Release]
Music provided by NoCopyrightSounds
Free Download/Stream: http://NCS.io/TopFloor
Watch: http://youtu.be/h-jxgXxRgnM