Name
Abstract | ||
|---|---|---|
We are seeing a remarkable watershed in the application of data science across markets and industries. A trifecta of advances in algorithms, cheap cycles, and the capture of networked data from everywhere are no doubt the catalysts. The results for many are continuous improvements in efficiencies, and for some are a fundamental re-imagination and disruption of just about every industry. This talk will give examples we are seeing (and funding!) for the latter, and then focus on our views of the ecosystem of value-from-data infrastructure and end-application companies. A big question is whether the enormous collective advances in tools, techniques and education are in-fact converting would-be differentiated products into democratized features used everywhere. We'll follow the value and make our own predictions on future as ML as a business. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1145/2939672.2945359 | KDD |
Keywords | Field | DocType |
Data Mining,Machine Learning,Data Science,Investing,Venture | Data mining,Computer science,Watershed,Product differentiation | Conference |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
1 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Greg Papadopoulos | 1 | 0 | 0.34 |