A past blog post explored using multi-layer-perceptrons (MLP) to predict stock prices using Tensorflow and Python. This post introduces another common library used for artificial neural networks (ANN) and other numerical purposes: Theano. An MLP Python class is created implemented using Theano, and then the performance of the class is compared with the TFANN class in a benchmark.
This post is part of a series on artificial neural networks (ANN) in TensorFlow and Python.
- Stock Market Prediction Using Multi-Layer Perceptrons With TensorFlow
- Stock Market Prediction in Python Part 2
- Visualizing Neural Network Performance on High-Dimensional Data
- Image Classification Using Convolutional Neural Networks in TensorFlow
In this post a multi-layer perceptron (MLP) class based on the TensorFlow library is discussed. The class is then applied to the problem of performing stock prediction given historical data. Note: This post is not meant to characterize how stock prediction is actually done; it is intended to demonstrate the TensorFlow library and MLPs.