Post-grad AI & AI programming coursework, neural network training and evaluation. Achieved 88%
Go to file
2021-03-19 17:21:00 +00:00
matlab template MatLab script from nnstart, saved dataset to csv for possible py use 2021-03-02 19:21:47 +00:00
report added template tensorflow notebook, added skeleton report 2021-03-02 23:06:09 +00:00
results exp2 draft, exporting results 2021-03-19 17:21:00 +00:00
.gitattributes Initial commit 2021-03-02 19:05:45 +00:00
.gitignore added template tensorflow notebook, added skeleton report 2021-03-02 23:06:09 +00:00
features.csv template MatLab script from nnstart, saved dataset to csv for possible py use 2021-03-02 19:21:47 +00:00
nncw.ipynb exp2 draft, exporting results 2021-03-19 17:21:00 +00:00
README.md exp2 draft, exporting results 2021-03-19 17:21:00 +00:00
scratchpad.ipynb exp2 draft, exporting results 2021-03-19 17:21:00 +00:00
targets.csv template MatLab script from nnstart, saved dataset to csv for possible py use 2021-03-02 19:21:47 +00:00

Shallow Neural Network Training Coursework

Evaluating a neural network using the MatLab cancer_dataset.

  1. Evaluate the network's tendency to overfit by varying the number of epochs and hidden layers being used
  2. Multiple classifier performance using majority vote
  3. Repeat 2 with two different optimisers (trainlm, trainrp)
  4. Extension: Distinguish between two equi-probable classes of overlapping 2D Gaussians