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Let's code a SNAKE GAME in python! 🐍
Let's code a SNAKE GAME in python! 🐍 121gamers 2 Views • 2 years ago

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

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Music promoted by Audio Library https://youtu.be/tDexBj46oNI
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Twelve Speed by - Slynk
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Build GUIs Using Python | Python Tkinter in 30 mins | Login App GUI
Build GUIs Using Python | Python Tkinter in 30 mins | Login App GUI 121gamers 2 Views • 2 years ago

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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Build a Stock Trend Prediction Web App in Python | GeeksforGeeks
Build a Stock Trend Prediction Web App in Python | GeeksforGeeks 121gamers 2 Views • 2 years ago

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.

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Chat with Multiple PDFs | LangChain App Tutorial in Python (Free LLMs and Embeddings)
Chat with Multiple PDFs | LangChain App Tutorial in Python (Free LLMs and Embeddings) 121gamers 2 Views • 2 years 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.

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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.

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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

Streamlit Python Course: Build a Machine Learning App to Predict Cancer
Streamlit Python Course: Build a Machine Learning App to Predict Cancer 121gamers 2 Views • 2 years 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.

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🔥 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

#python #streamlit #MachineLearning #DataScience

Bind to the Cloud with Falcor with Jafar Husain at Modern Web UI
Bind to the Cloud with Falcor with Jafar Husain at Modern Web UI 121gamers 2 Views • 2 years ago

SLIDES: https://drive.google.com/open?....id=0B7zweKma2uL1c1pN

Jafar Husain is the Cross-Team Technical Lead for the Netflix UI's. He is the architect of Netflix's UI data platform "Falcor", and specializes in building reactive, event-driven systems. He is the Netflix representative on the JavaScript standards committee (TC-39) and is actively working to evolve the JavaScript language.

Imagine how easy building your application would be if all of the data in the cloud was available in-memory on the client.
Falcor is the JS data access framework that powers Netflix. We'll show you how to use Falcor to replace all of your endpoints a with a single JSON resource on the server. Then we'll show you how to use the power of Angular 2 templates to bind your templates directly to your JSON resource in cloud without any code at all! You'll see how simple app development can be when your controllers don't have to worry about retrieving data from the server.

You'll also see how easy it is to integrate Falcor into your existing stack, regardless of whether you are using a single database, or like Netflix, have a huge number of different back-end services.

AWS Tutorial 3 - How to Install XAMPP Server on EC2 Windows Server at AWS EC2 Instance
AWS Tutorial 3 - How to Install XAMPP Server on EC2 Windows Server at AWS EC2 Instance 121gamers 2 Views • 2 years ago

Hi guys, let's see how to install the XAMPP server on a Windows EC2 machine. Launch Windows Ec2 instance on EC2 Instance. You will also learn how to host a website on the Ec2 Windows machine.

How to Launch Windows Machine on EC2
https://youtu.be/l2q7pSz8l1E

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How I Became a Top Tier Solo Raider In Deadside
How I Became a Top Tier Solo Raider In Deadside 121gamers 2 Views • 5 months ago

Deadside 1.5
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