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This case study shows how to create a model for text analysis and classification and deploy it as a web service in Azure cloud in order to automatically classify support tickets. This project is a proof of concept made by Microsoft (Commercial Software Engineering team) in collaboration with Endava http://endava.com/en
Text classification using various techniques, including Naive Bayes and Passive Aggressive classifiers, along with different vectorization methods such as Count Vectorization
Proteins have different family types, this modal determine a protein's family type based on sequence. Inspired by search engines such as BLAST which has this capability, but it want to try out and see if a machine learning approach can do a good job in classifying a protein's family based on the protein sequence.
Rating: (6/10) The project uses Python libraries and APIs to analyze Reddit data, predict user input, suggest new titles based on cosine similarity, calculate combined scores, and output the best suggestion.