What do you see as the downside of creating this organization now, as opposed to in 100 years? Artificial Intelligence in its current state has shown itself to be incredibly useful and effective at small tasks. I see no harm in researching and expanding this field (besides opportunity cost).
Also, I see a distinct lack of "fear-mongering" in this post.
It would be really interesting to see a visualization (maybe using PCA) of the LDA vectors for each document. The topics are not super convincing that the LDA approach worked well.
Other than that, this is a good intro to NLP and calculating document similarity. Well done!
if you want to learn neural nets check out Karpathy's class (cs231n.github.io) and do the assignments. making a github repo and HN post about using neural networks is false self-advertising and illegitimatizes those of us who know what we are talking about.
this doesn't look like a neural net to me. from NeuralNetwork.py
from sklearn.neighbors import KNeighborsClassifier
# Create a sperate neural network for each identifier
for index in range(0, len(NaturalLanguageObject._Identifiers)):
nn = KNeighborsClassifier()
self._Networks.append(nn)
Also, I see a distinct lack of "fear-mongering" in this post.