Source: Deep Learning on Medium
A weekly newsletter with the latest developments in Data Science and Machine Learning and Artificial Intelligence.
Oct 27, 2019
Welcome to the latest edition of Sunday Briefing. This week we are taking a look at some of the less explored aspects of math and data science with a History of Mathematics, a nice post on Linear Programming, some advice on how to generate labels for unlabeled data and a comparison of statistical and mathematical modeling approaches.
We also consider a paper discussing the limitations of current neuroscience approaches by applying them to relatively simple CPUs, a new library for Graph Statistics in Python and a general framework for sampling temporal networks in an unbiased way.
Finally, in our video of the week Joe Jevnik guides us through a 2017 tutorial on using Neural Networks for Time Series Prediction.
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The D4S team
Tutorials and blog posts that came across our desk this week.
- My 2019 Mathematics A To Z: Linear Programming [nebusresearch.wordpress.com]
- A Very Brief (visual) History of Mathematics [medium.com/@marksaroufim]
- Google Data Commons [datacommons.org]
- The Risks of AutoML and How to Avoid Them [hbr.org]
- Quantum Supremacy Using a Programmable Superconducting Processor [ai.googleblog.com]
- The Next Word — Where will predictive text take us? [newyorker.com]
- Lots of Data, No Labels, Now What? [ODSC]
Fresh off the press:
Some of the most interesting academic papers published recently.
- 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)
Video of the week:
Interesting discussions, ideas or tutorials that came across our desk.
A Worked Example of Using Neural Networks for Time Series Prediction
Opportunities to learn from us
- Oct 30, 2019 — Applied Probability Theory from Scratch [SOLD OUT]
- Nov 11, 2019 — Natural Language Processing (NLP) from Scratch [Register]
- Nov 18, 2019 — Graphs and Network Algorithms from Scratch [Register] 🆕
- Dec 04, 2019 — Data Visualization with matplotlib and seaborn [Register] 🆕
- Dec 11, 2019 — Deep Learning From Scratch [Register] 🆕
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