<description>&lt;p&gt;Our guest on this episode is Dr. Patrick Riley from Google Accelerated Science.&lt;br/&gt;&lt;br/&gt;Some relevant papers and links:&lt;/p&gt;&lt;ul&gt;&lt;li&gt;Riley, P., &lt;b&gt;Practical advice for analysis of large, complex data sets. &lt;/b&gt;&lt;em&gt;The Unofficial Google Data Science Blog&lt;/em&gt;, &lt;a href='http://www.unofficialgoogledatascience.com/2016/10/practical-advice-for-analysis-of-large.html'&gt;www.unofficialgoogledatascience.com/2016/10/practical-advice-for-analysis-of-large.html&lt;/a&gt; (2016)&lt;/li&gt;&lt;li&gt;Zinkevich, M., &lt;b&gt;Rules of Machine Learning: Best Practices for ML Engineering.&lt;/b&gt; &lt;a href='https://developers.google.com/machine-learning/guides/rules-of-ml/'&gt;https://developers.google.com/machine-learning/guides/rules-of-ml/&lt;/a&gt; (last updated Oct 2018)&lt;/li&gt;&lt;li&gt;Wigner, E., &lt;b&gt;The Unreasonable Effectiveness of Mathematics in the Natural Sciences.&lt;/b&gt; &lt;em&gt;Communications in Pure and Applied Mathematics, &lt;/em&gt;doi:10.1002/cpa.3160130102 (1960)&lt;/li&gt;&lt;li&gt;Gulshan, V., Peng, L, Coram, M., &lt;b&gt;Development and Validation of a Deep Learning Algorithm for Detection of Diabetic Retinopathy in Retinal Fundus Photographs.&lt;/b&gt; &lt;em&gt;The Journal of the American Medical Association&lt;/em&gt;, doi:10.1001/jama.2016.17216 (2016)&lt;/li&gt;&lt;/ul&gt;&lt;p&gt;&lt;br/&gt;Google Accelerated Science website: &lt;a href='http://ai.google/research/teams/applied-science/gas'&gt;ai.google/research/teams/applied-science/gas&lt;/a&gt;&lt;/p&gt;</description>

Materials and Megabytes

Stanford Materials Computation and Theory Group, Qian Yang's lab at the University of Connecticut

Patrick Riley (Season 2, Ep. 3)

FEB 15, 201924 MIN
Materials and Megabytes

Patrick Riley (Season 2, Ep. 3)

FEB 15, 201924 MIN

Description

Our guest on this episode is Dr. Patrick Riley from Google Accelerated Science.

Some relevant papers and links:

  • Riley, P., Practical advice for analysis of large, complex data sets. The Unofficial Google Data Science Blog, www.unofficialgoogledatascience.com/2016/10/practical-advice-for-analysis-of-large.html (2016)
  • Zinkevich, M., Rules of Machine Learning: Best Practices for ML Engineering. https://developers.google.com/machine-learning/guides/rules-of-ml/ (last updated Oct 2018)
  • Wigner, E., The Unreasonable Effectiveness of Mathematics in the Natural Sciences. Communications in Pure and Applied Mathematics, doi:10.1002/cpa.3160130102 (1960)
  • Gulshan, V., Peng, L, Coram, M., Development and Validation of a Deep Learning Algorithm for Detection of Diabetic Retinopathy in Retinal Fundus Photographs. The Journal of the American Medical Association, doi:10.1001/jama.2016.17216 (2016)


Google Accelerated Science website: ai.google/research/teams/applied-science/gas