Write a Technical Report - Neural Networks
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I want well commented code for the following algorithms:
1. K-means clustering.
2. Latent Dirichlet Allocation.
3. Collaborative filtering.
4. Matrix factorization using coordinate descent.
Also, a short writeup on how the algorithm works. About 50-100 words for each of the algorithms mentioned above.
The first two algorithms are clustering algorithms while the third and the fourth ones are applied in recommender systems. Use dataset to train these algorithms and show the results of the trained algorithms in terms of an appropriate metric. An appropriate metric is important as the performance of the two pairs of algorithms have to be compared. For example, accuracy could be used for the first two algorithms and a precision-recall curve for the third and the fourth. Explain the dataset that is used to train the algorithms and the results either in comments or in a separate document.
Use pandas or Sframes for datasets to maintain compatibility with the rest of our code.
I can provide data for cases where you aren’t able to find any online, but that would not be preferable. Please document properly the sources for the data.
- The New York Times
- Wall Street Journal
- Times Online