Machine learning project

The project was done in collaboration with Michele Cafagna For more information please read the report.

Professor's request

• Randomly initialised weights
• Try a minimum number of initial configurations (e.g. 10 test frameworks)
• The test examples must be provided randomly
• Momentum
• Check the learning curve (draw it with each test)
• Use average gradients (eta/l), especially if using mini batch NN-part2 slide 25
• Optimisation
• Stopping criteria, in any case stop after too large a number of epochs
• Regularisation
• Use heuristics (slide)