Machine Learning/AI: Hard Facts, Conclusions and Actions
How safe it is to dive into the deep end - what’s real and what isn’t
Which platforms and applications to invest in first
Where innovation in open source and with citizen data scientist enablement is having an impact
We are in the early stages of a 10-year cycle which machine learning is morphing from a lab curiosity to a rich, pervasive technology value-add. Grandiose visions and deep seated cynicism are fighting each other in the marketplace. We break down fact versus fiction and various alternative paths to success.