Issue #22
October 27, 2019
- 1. My 2019 Mathematics A To Z: Linear Programming [nebusresearch.wordpress.com]
- 2. A Very Brief (visual) History of Mathematics [medium.com/@marksaroufim]
- 3. Google Data Commons [datacommons.org]
- 4. The Risks of AutoML and How to Avoid Them [hbr.org]
- 5. Quantum Supremacy Using a Programmable Superconducting Processor [ai.googleblog.com]
- 6. The Next Word - Where will predictive text take us? [newyorker.com]
- 7. Lots of Data, No Labels, Now What? [ODSC]
- • Could a Neuroscientist Understand a Microprocessor? (E. Jonas, K. P. Kording)
- • Hierarchical organization of urban mobility and its connection with city livability (A. Bassolas, H. Barbosa-Filho, B. Dickinson, X. Dotiwalla, P. Eastham, R. Gallotti, G. Ghoshal, B. Gipson, S. A. Hazarie, H. Kautz, O. Kucuktunc, A. Lieber, A. Sadilek, J. J. Ramasco)
- • Temporal Network Sampling (N. K. Ahmed, N. Duffield, R. A. Rossi)
- • GraSPy: Graph Statistics in Python (J. Chung, B. D. Pedigo, E. W. Bridgeford, B. K. Varjavand, H. S. Helm, J. T. Vogelstein)
- • A short comment on statistical versus mathematical modelling (A. Saltelli)
- • Principal Component Analysis: A Generalized Gini Approach (A. Charpentier, S. Mussard, T. Ouraga)
Joe Jevnik - A Worked Example of Using Neural Networks for Time Series Prediction
All our videos are also available in our YouTube playlist.
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