An attempt to use machine learning to recognize handwritten words and translate them into correct unicode equivalents.

• Research appropriate machine learning algorithms.
• Implement machine learning algorithm on basic set.
  • Create neural networks with the ability to expand to n layers with m neurons per layer.
  • Apply back propagation to neural networks.
  • Train feed forward neural networks to act as logic gates.
• Implement machine learning algorithm on training set.
  • Gather images to be used for training set.
  • Standardize input characters.
  • Generate receptors to be used as neural network input.
  • Train neural networks using training set.
• Implement machine learning algorithm on real world set.
  • Predict new characters using trained neural networks.
• Profit