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This repo contains unsupervised models including the Latent Dirichlet Allocation (LDA) model applied to a corpus of research papers and a clustering analysis applied to customer segmentation.

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Unsupervised Learning

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Notebooks and descriptions

Notebook Brief Description
topic-modeling In this notebook, I will use Python and its libraries for topic modeling. In topic modeling, statistical models are used to identify topics or categories in a document or a set of documents. I will use one specific method called Latent Dirichlet Allocation (LDA) and apply it to labels on research papers.
clustering-for-customer-segmentation In this project I will apply clustering algorithms to the dataset Wholesale Customers Data Set from the UCI Machine Learning Repository. The dataset contains customers' spending amounts of several product categories.
network-analysis Neural networks tutorial where I build fully-connected networks and convolutional neural networks using both Keras and TensorFlow respectively (in progress).
transfer-learning-mini-tutorial A tutorial on network analysis.

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This repo contains unsupervised models including the Latent Dirichlet Allocation (LDA) model applied to a corpus of research papers and a clustering analysis applied to customer segmentation.

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