The Master Algorithm
In this week's episode, Kyle Polich interviews Pedro Domingos about his book, The Master Algorithm: How the quest for the ultimate learning machine will remake our world. In the book, Domingos describ...
16 Mar 201846min
The No Free Lunch Theorems
What's the best machine learning algorithm to use? I hear that XGBoost wins most of the Kaggle competitions that aren't won with deep learning. Should I just use XGBoost all the time? That might work ...
9 Mar 201827min
ML at Sloan Kettering Cancer Center
For a long time, physicians have recognized that the tools they have aren't powerful enough to treat complex diseases, like cancer. In addition to data science and models, clinicians also needed actua...
2 Mar 201838min
Optimal Decision Making with POMDPs
In a previous episode, we discussed Markov Decision Processes or MDPs, a framework for decision making and planning. This episode explores the generalization Partially Observable MDPs (POMDPs) which a...
23 Feb 201818min
AI Decision-Making
Making a decision is a complex task. Today's guest Dongho Kim discusses how he and his team at Prowler has been building a platform that will be accessible by way of APIs and a set of pre-made scripts...
16 Feb 201842min
[MINI] Reinforcement Learning
In many real world situations, a person/agent doesn't necessarily know their own objectives or the mechanics of the world they're interacting with. However, if the agent receives rewards which are cor...
9 Feb 201823min
Evolutionary Computation
In this week's episode, Kyle is joined by Risto Miikkulainen, a professor of computer science and neuroscience at the University of Texas at Austin. They talk about evolutionary computation, its appli...
2 Feb 201824min
[MINI] Markov Decision Processes
Formally, an MDP is defined as the tuple containing states, actions, the transition function, and the reward function. This podcast examines each of these and presents them in the context of simple ex...
26 Jan 201820min
