Top videos | Cash In Vids Make Money From Vids And Vloging CashInVids CashInVids.com

Home
Articles

Top videos

All Time

Today

This week

This month

This year

Make first android app with python 121gamers 0 Views • 1 year ago

Get Free GPT4o from https://codegive.com
to create your first android app using python, you can use the kivy framework. kivy is an open-source python library for rapid development of multi-touch applications. it allows you to build cross-platform applications for android, ios, windows, linux, and macos. in this tutorial, we will walk you through creating a simple android app using python and kivy.

step 1: install kivy
first, you need to install kivy on your system. you can install kivy using pip by running the following command in your terminal or command prompt:

step 2: create the python script
create a new python script for your android app. you can use any text editor or an ide of your choice. here is a simple example of a python script that creates a basic kivy app:

in this script, we are creating a simple kivy app with a single button that displays the text "hello, kivy!".

step 3: build the android app
to build your python script into an android app, you can use tools like buildozer. buildozer is a tool that automates the process of building and packaging kivy applications for various platforms, including android.

first, install buildozer using pip:

next, create a `buildozer.spec` file in the same directory as your python script. this file contains the configuration settings for building your android app. here is an example `buildozer.spec` file for our simple app:

finally, run the following command to build your android app using buildozer:

this command will compile your python script, package it as an android app, deploy it to a connected android device or emulator, and run the app.

congratulations! you have successfully created your first android app using python and kivy. feel free to explore more features of kivy and customize your app further.

...

#python android ide
#python android
#python android adb
#python android apk
#python android app development

python android ide
python android
python android adb
python android apk
python android app development
python android emulator
python android studio
python android automation
python android bluetooth
python android app
python append to array
python apply lambda
python apply function
python append to file
python app
python append to dictionary
python append to list
python append

Chat with Multiple PDFs | LangChain App Tutorial in Python (Free LLMs and Embeddings) 121gamers 0 Views • 1 year ago

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

Android App using Python | Convert .Py to APK | #Kivy Tutorial 121gamers 0 Views • 1 year ago

Hello, Guys, I am Spidy. I am back with another video.

In this video, I am showing you how you can make a Cross-Platform app using python, which means a single app for windows & android. Here we are creating GUI using Kivy for windows then we are converting python code to APK.

🔥 SUBSCRIBE FOR MORE VIDEOS ► https://bit.ly/2UvLDcQ | ★

Code:- https://github.com/Spidy20/Python_To_APK
Give Star to repository & follow me on Github

Other Kivy Android App Tutorial:- https://www.youtube.com/playli....st?list=PLsT53VV2LII

Like & Share this video and share this video with your friends.

My Github for free projects:- https://github.com/Spidy20
My store for buying paid project:- https://www.instamojo.com/kushalbhavs...
In this store, you can download various mini projects & a big project at a lower rate.

ML Guidelines PDF:- https://imojo.in/27qk1iu

Like the video & Subscribe channel and comment down your review about it.
Subscribe to Machine Learning Hub for more exciting videos.

Follow our community on Instagram for Video updates and ML-related Posts:- https://www.instagram.com/machine_lea...

Donate us via UPI: - kushalbhavsar58@okicici
Donate us via Paypal: - https://www.paypal.com/paypalme/spidy1820

Do Subscribe.

Android ML App Development:- https://www.youtube.com/playlist?list...
OpenCV Tutorials:- https://www.youtube.com/playlist?list...
ChatBot Development:- https://www.youtube.com/playlist?list...
Deep Learning Projects:- https://www.youtube.com/playlist?list...
Python Projects:- https://www.youtube.com/playlist?list...
Face Recognition Project:- https://www.youtube.com/playlist?list...
Food recognition WebApp using Flask:- https://www.youtube.com/playlist?list...
Flask Tutorial Playlist:- https://www.youtube.com/playlist?list...
Google News Web Scraping Tutorial:- https://youtu.be/HSimiUPsDEk
Wikipedia App using Python:- https://youtu.be/_kpKvcJ9vJI
Car Detection System:- https://www.youtube.com/playlist?list...
Create ML App from scratch:- https://www.youtube.com/playlist?list...
AI Playing Flappy Bird Full Tutorial:- https://www.youtube.com/playlist?list...
Mask RCNN full Playlist:- https://www.youtube.com/playlist?list...
Emotions Recognition Full Tutorials Playlist:- https://www.youtube.com/playlist?list...
Tensorflow Object Detection full Tutorial Playlist:- https://www.youtube.com/playlist?list...
Face Mask Detection using TF Object Detection API - https://www.youtube.com/playlist?list...
OpenPose Estimation Full tutorial:-
https://www.youtube.com/playlist?list...

Do follow me, comment down your opinion & suggestions.
Tell me if you didn't get anything.

I will be back with another python tricks & tips
Subscribe to our Channel & press the bell icon

You will get the all notification of the channel on my Instagram page.
Follow me on Github for more projects related to Machine learning and Deep learning
Buy Coffee for me:- https://www.buymeacoffee.com/spidy20

*Until that "Keep learning, Do more code!"*
*"Stay safe at home, keep coding"*

android app using python. python to apk, android app python, .py to .apk, kivy tutorial python, kivy python, kivy, kivymd python, android app tutorial, kivy android app development, develop android app using kivy python, kivy python, machine learning hub, kivy tutorial for beginner, python to android app. how to create android app using python

"The video thumbnails were created using publicly available images from Google images and are used solely for thumbnail purposes. I do not claim ownership of these images. If you are the owner of any copyrighted content used in these thumbnails and want them removed or changed, please contact me and I will comply promptly. Thank you."

#androidappusingpython
#kivy
#kivytutorial

Streamlit Python Course: Build a Machine Learning App to Predict Cancer 121gamers 0 Views • 1 year ago

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!

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

#python #streamlit #MachineLearning #DataScience