I've made a similar list for economists. It included a list of practical applications of ML. Developers can get a sense of what the discipline can do before jum

I've made a similar list for economists. It included a list of practical applications of ML. Developers can get a sense of what the discipline can do before jumping in. APPLIED MACHINE LEARNING CASES ## Business 1. Kaggle, Data Science Use cases. An outline of business applications. Few companies have the data to implement these things. https://www.kaggle.com/wiki/DataScienceUseCases https://www.kaggle.com/wiki/DataScienceUseCases 2. Kaggle, Competitions. (Make sure you chose “All Competitions” and then “Completed”.) Each competition has a leaderboard. When users publish their solutions on GitHub, you can find links to these solutions on the leaderboard. https://www.kaggle.com/competitions https://www.kaggle.com/competitions Industrial solutions are more powerful and complex than these examples, but they are not publicly available. Data-driven companies post some details about this work in their blogs. ## Emerging applications 1. Stanford’s CS229 Course, Student projects. See “Recent years’ projects.” Hundreds of short papers. http://cs229.stanford.edu/ http://cs229.stanford.edu/ 2. CMU ML Department, Student projects. More advanced problems, compared to CS229. http://www.ml.cmu.edu/research/data-analysis-projects.html http://www.ml.cmu.edu/research/data-analysis-projects.html 3. arXiv, Machine Learning. Drafts of important papers appear here first. Then they got published in journals. http://arxiv.org/list/stat.ML/recent http://arxiv.org/list/stat.ML/recent 4. CS journals. Applied ML research also appear in engineering journals. https://scholar.google.com/citations?view_op=top_venues&hl=en&vq=eng_theoreticalcomputerscience https://scholar.google.com/citations?view_op=top_venues&hl=e... 5. CS departments. For example: CMU ML Department, PhD dissertations. http://www.ml.cmu.edu/research/phd-dissertations.html http://www.ml.cmu.edu/research/phd-dissertations.html ## Government 1. Bloomberg and Flowers, “NYC Analytics.” NYC Mayor’s Office of Data Analysis describes their data management system and improvements in operations. http://www.nyc.gov/html/analytics/downloads/pdf/annual_report_2013.pdf http://www.nyc.gov/html/analytics/downloads/pdf/annual_repor... 2. UK Government, Tax Agent Segmentation. https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/396175/Report348.pdf https://www.gov.uk/government/uploads/system/uploads/attachm... 3. Data.gov, Applications. Some are ML-based. http://www.data.gov/applications http://www.data.gov/applications 4. StackExchange, Applications. http://opendata.stackexchange.com/questions/3346/examples-of-useful-applications-that-are-being-developed-using-open-data http://opendata.stackexchange.com/questions/3346/examples-of... ## See also The original article: https://antontarasenko.com/2015/12/28/machine-learning-for-economists-an-introduction/ https://antontarasenko.com/2015/12/28/machine-learning-for-e... A related list of cases: https://www.quora.com/What-are-some-practical-applications-of-big-data/answer/Anton-Tarasenko-2?srid=i9vl https://www.quora.com/What-are-some-practical-applications-o...