Part 2 of supercharge your Python Project with AI: RNN-LSTM & KNN Models Explained!

Welcome to this second part of an exciting 2-part series where I’ll show you how to implement AI into your own Python project! 🚀 By following along, you’ll save time and effort because I’ve already done the heavy lifting — testing, failing, and refining with the help of ChatGPT.

In this video, we’ll dive into all four crucial steps for creating and training two powerful AI models: an RNN-LSTM model and a KNN model. Whether you're building an AI trading bot, experimenting with machine learning, or simply exploring AI integration, this video is packed with practical insights and clear guidance to help you get started.

👉 What You’ll Learn:

Preparing your data for AI training.
Building an RNN-LSTM model from scratch.
Implementing and fine-tuning a KNN model.
Integrating your AI models seamlessly into a Python project.
Stay tuned for Part 2, where we’ll dive deeper into fine-tuning and real-world applications. Don’t forget to like, subscribe, and hit the bell icon 🔔 so you don’t miss out! Let's make AI accessible and functional for your projects! 💻✨
#nasdaq #pythonprogramming #passiveincome #automation #tradingbot

View the bot in action at:   / nasdaqscalpingbot  
Weekdays 22:00(10 pm) - 23:00 (11pm) CE

The discord channel:
  / discord  

0:00 - Intro
3:39 - RNN models
18:12 - Test your model for the first time
20:12 - The output of your training
23:33 - Tips to enhance your precision
43:15 - Traininga KNN model
47:40 - Outro