MathGeniusAI is a cutting-edge project that leverages AI technologies to solve elementary and middle school math problems with an astounding accuracy rate of over 90%. The project focuses on engineered AI models, employing network architectures such as Long Short-Term Memory (LSTM), Bidirectional Encoder Representations from Transformers (BERT), Recurrent Neural Networks (RNN), and Transformer models.
- AI-powered math problem-solving with accuracy exceeding 90%.
- Utilization of advanced neural network architectures: LSTM, BERT, RNN, and Transformer.
- Comprehensive coverage of elementary and middle school mathematics.
- Experimentation with cutting-edge AI models to achieve exceptional performance.
- Python: The core programming language for implementing AI algorithms.
- TensorFlow: An open-source machine learning framework for constructing neural network architectures.
- Keras: A high-level neural networks API that interfaces with TensorFlow for rapid model development.
- PyTorch: A deep learning framework that facilitates building dynamic neural networks with ease.
- SciPy: A library for scientific and technical computing that provides tools for data analysis and manipulation.
- NumPy: A fundamental package for numerical computations in Python.
- Matplotlib: A data visualization library used for creating static, interactive, and animated visualizations in Python.
Created by Nilansh Dey Ghosh.