Building Stock Prediction Tool: PyTorch, Fast API, React & Warp Tutorial
- Authors
- Published on
- Published on
In this exhilarating tutorial by NeuralNine, brace yourself as they embark on a thrilling journey to construct a cutting-edge stock prediction tool using a formidable array of technologies. With PyTorch as their trusty steed for training, they forge ahead, backed by the robust Fast API for the backend and the sleek React with TypeScript for the frontend. Docker and Engine X stand as their loyal companions, ready to deploy their creation into the digital battlefield.
Enter Warp, a coding assistant akin to having a skilled co-driver in a high-octane rally. NeuralNine doesn't just talk the talk; they walk the walk, demonstrating the power of Warp in real-time coding. Witness the birth of an AI stock prediction tool, where ticker symbols like Apple and Microsoft dance on the screen, their fortunes predicted by the machine's digital brain. But remember, this is no crystal ball; it's a tool for learning and exploration, not for high-stakes trading.
As the team delves into the intricacies of training their model using PyTorch and Y Finance, they navigate through technical waters, charting a course with SMA, EMA, RSI, MACD, and more. With Warp by their side, they deftly maneuver through data preparation, model training, and architecture design, crafting a masterpiece of neural networks and attention mechanisms. And when the road gets bumpy, they take the wheel, tweaking parameters and ensuring a smooth ride to success.
But the adventure doesn't end there. NeuralNine shifts gears, transitioning to the creation of a Fast API application around their trained model, setting the stage for seamless interaction via an API. CORS is the name of the game as they navigate the complexities of backend development, ensuring that their creation is not just a static display but a dynamic tool ready to serve predictions at a moment's notice. With Warp as their guide, they navigate the twists and turns of coding, building a bridge between data science and user experience, all in the quest for innovation and knowledge.
Image copyright Youtube
Image copyright Youtube
Image copyright Youtube
Image copyright Youtube
Watch Coding A Full Stock Prediction Tool By Prompt (Warp, Python, React) on Youtube
Viewer Reactions for Coding A Full Stock Prediction Tool By Prompt (Warp, Python, React)
Warp, the coding assistant, started as an enhanced terminal
Request for a video on Tradingview API
Interest in seeing the approach to a similar project
Request for more prompt/vibe coding tutorials
Positive feedback on the video
Appreciation for sharing the content
Compliments on the video
General positive reactions to the video
Related Articles
Building Stock Prediction Tool: PyTorch, Fast API, React & Warp Tutorial
NeuralNine constructs a stock prediction tool using PyTorch, Fast API, React, and Warp. The tutorial showcases training the model, building the backend, and deploying the application with Docker. Witness the power of AI in predicting stock prices with this comprehensive guide.
Exploring Arch Linux: Customization, Updates, and Troubleshooting Tips
NeuralNine explores the switch to Arch Linux for cutting-edge updates and customization, detailing the manual setup process, troubleshooting tips, and the benefits of the Arch User Repository.
Master Application Monitoring: Prometheus & Graphfana Tutorial
Learn to monitor applications professionally using Prometheus and Graphfana in Python with NeuralNine. This tutorial guides you through setting up a Flask app, tracking metrics, handling exceptions, and visualizing data. Dive into the world of application monitoring with this comprehensive guide.
Mastering Logistic Regression: Python Implementation for Precise Class Predictions
NeuralNine explores logistic regression, a classification algorithm revealing probabilities for class indices. From parameters to sigmoid functions, dive into the mathematical depths for accurate predictions in Python.