Why do we need it. How does it work. Where is it used.
What are they. Why do we need them. Where are they used.
List of tasks that appear in an ML practitioner's day-to-day. Insights on how to build products that perform those tasks.
What it's all about. Why is it important. How it's used in the real world.
A deep dive into notebook products
What is it. Why do we need to measure it. Metrics that can used.
What is it. Why do we need it. List of tools available.
What is risk. True risk vs empirical risk. How to minimize empirical risk.
List of ideas for AI infrastructure builders to consider
Why do we need it. What is it. Types of activation functions.
Pricing levers. Valley of death. Customer acquisition playbook.
Lyft's self-driving cars, detecting Parkinson's disease from breathing patterns, making air conditioners 10x better, self-taught AI, generating protein…