[جلد ۱۳۲ شماره ۱] ماهنامه ریاضی آمریکایی

00-Introduction to the Special Issue 01-Becoming a Data Scientist_ An Impractical Guide Mission Statement. A Young Mathematician. Something Else Was A'Brewing. ``Going Into Industry''. The Life of an Academic Data Scientist. Lessons Learned. 02-A Generalization of Bonse_s Inequality 03-An Invitation to the Euler Characteristic Transform Introduction. The ECT. A fern leaf example. Some modifications and applications. Some notes on matrix representations. The SECT. Parameterized families of ECTs. Computational considerations. Reconstruction. Instances of ECT in deep learning. Conclusion. 04-Uncovering the Euclidean Geometry of Data Introduction. Examples. Voting patterns. Strings of text. The math. Conclusion. 05-Yet the Riemann Zeta Function at Positive Even Integers 06-Diversity_ Identity_ and Data Introduction. Mathematical Framework. Data. Results and Discussion. Conclusion. 07-Modeling _ Optimization for Streaming Listening Demand ``Nile, Make me a hit like Bowie's'': A Simple Dynamic Model for Streaming Song Listening. Streaming demand as a counting process. Other counting process for streaming demand. Model for listener affinity. Song demand via listening mode. The importance of audience segmentation. ``Just because a record has a groove, don't make it in the groove'': Covariate Models for Processes & Forecasting. Fully Bayesian workflow for streaming demand. Null model ADSR/forced model ``Whip It'': Fully Optimizing Listening Demand. Null model. ADSR model. Comments and Recommendations. 08-The Matrix Equation X3 _ Y3 _ 2Z3 09-Sports Analytics Double Take_ The Need for Multiple Perspectives on Data Baffling box score. Tracking the NBA. Lifting the Veil of Summary Statistics. Who's #1? Final take. 10-Launching a Data Analytics Major_ How Collaboration and Agility Built a Successful Program Introduction. Summer Study Group. The Revolutionary Challenge. Approval of the Data Analytics Major. The First Three Years. Going Forward. Conclusion and Recommendations. 11-100 Years Ago This Month in The American Mathematical Monthly 12-Problems and Solutions 13-Reviews Introduction. Where does your data come from? How do you visualize data? How do you support others in exploring data? How do you make your process inclusive? Conclusion.