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Minerva AI (EN)
  • 👋Welcome to Minerva AI
  • STUDIES & FINDINGS
    • ☝️Abstract
    • 📍Introduction and related works
    • 💡Model overview
      • ♾️Convolutional neural network - CNN
      • ✍️Dropout techniques
      • 🧠Long short-term memory (LSTM)
      • 🙆Methodology
      • 🔗Data collection and merging
      • 🛠️Model architecture
      • ➕Dataset and Parameter Optimization
      • 👌Results and discussion
      • ⚓Trading Philosophy & Method
      • ➗Basic algorithm
      • 🌠Results
    • 👉Conclusion
  • PRODUCT DEVELOPMENT
    • 👀Vision and development roadmap
    • 🌟Revenue models
    • 🪙Tokenomics
  • TEAM
    • 👥Founding team
  • RESOURCES
    • 📗References
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  1. STUDIES & FINDINGS

Model overview

PreviousIntroduction and related worksNextConvolutional neural network - CNN

Last updated 1 year ago

In this paper, we utilized a combination of CNN and LSTM layers. Therefore, before presenting our methodology, we will introduce the concepts of CNN and LSTM.

Our findings

Get Started

💡
♾️Convolutional neural network - CNN
✍️Dropout techniques
🧠Long short-term memory (LSTM)
🙆Methodology
🔗Data collection and merging
🛠️Model architecture
➕Dataset and Parameter Optimization
👌Results and discussion
⚓Trading Philosophy & Method
➗Basic algorithm
🌠Results