Machine learning: pitfalls and opportunities
By: Paul Ebreo
Experience Level: Intermediate
Length: 45 Minutes
Part 1a. What is ai / ml?
Part 1b. Limitations of current approach
The current way of doing ML is necessary but limited. If we truly want "intelligence", we need a new way of doing things i.e. an AI that can think beyond its training, an AI that requires much less data, and an AI that is much more adaptable than current AI. Here we give case studies of current AI systems and biology highlighting the limitations and potential of what a real intelligent system looks like.
Part 1c. The upcoming AI / ML winter
Part 2a. What does python have to do with ML?
Part 2b. The new approach to ML
What use is Python at all? Is it possible to conceptualize ML with or without python? In this section, I explain how Python is used to conceive AI/ML. Then I propose a new way of approaching the problem. I explain the various ways Python is used in ML from deep learning, reinforcement learning etc.
Part 3. A new way of thinking
In this section, I propose a different way of thinking of the problem and propose a solution.