NumPy Powers Stock Prediction: A Deep Dive into DNN for Yen-to-Nikkei Forecasting
Analysis
This article showcases an exciting application of Deep Neural Networks (DNN) using only NumPy, demonstrating the power of fundamental tools in machine learning. It provides a detailed breakdown of how to build a model that predicts the Nikkei average from the USD/JPY exchange rate, offering valuable insights into the inner workings of DNNs.
Key Takeaways
- •DNNs are implemented using only NumPy, showcasing the foundational power of this library.
- •The model predicts the Nikkei average from USD/JPY exchange rates, providing a practical financial application.
- •The article emphasizes understanding the inner workings of the DNN, including the backpropagation of errors and gradient descent.
Reference / Citation
View Original"This article implements a Deep Neural Network (DNN) using only NumPy, without frameworks (PyTorch or TensorFlow), to create a model that predicts the Nikkei stock average from the exchange rate (USD/JPY)."
Q
Qiita MLFeb 1, 2026 16:51
* Cited for critical analysis under Article 32.