Data Skeptic

Data Skeptic

The Data Skeptic Podcast features interviews and discussion of topics related to data science, statistics, machine learning, artificial intelligence and the like, all from the perspective of applying critical thinking and the scientific method to evaluate the veracity of claims and efficacy of approaches.

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Episoder(605)

Quantum Computing

Quantum Computing

In this week's episode, Scott Aaronson, a professor at the University of Texas at Austin, explains what a quantum computer is, various possible applications, the types of problems they are good at sol...

1 Des 201747min

Azure Databricks

Azure Databricks

I sat down with Ali Ghodsi, CEO and found of Databricks, and John Chirapurath, GM for Data Platform Marketing at Microsoft related to the recent announcement of Azure Databricks. When I heard about th...

28 Nov 201728min

[MINI] Exponential Time Algorithms

[MINI] Exponential Time Algorithms

In this episode we discuss the complexity class of EXP-Time which contains algorithms which require $O(2^{p(n)})$ time to run.  In other words, the worst case runtime is exponential in some polynomial...

24 Nov 201715min

P vs NP

P vs NP

In this week's episode, host Kyle Polich interviews author Lance Fortnow about whether P will ever be equal to NP and solve all of life's problems. Fortnow begins the discussion with the example quest...

17 Nov 201738min

[MINI] Sudoku \in NP

[MINI] Sudoku \in NP

Algorithms with similar runtimes are said to be in the same complexity class. That runtime is measured in the how many steps an algorithm takes relative to the input size. The class P contains all alg...

10 Nov 201718min

The Computational Complexity of Machine Learning

The Computational Complexity of Machine Learning

In this episode, Professor Michael Kearns from the University of Pennsylvania joins host Kyle Polich to talk about the computational complexity of machine learning, complexity in game theory, and algo...

3 Nov 201747min

[MINI] Turing Machines

[MINI] Turing Machines

TMs are a model of computation at the heart of algorithmic analysis.  A Turing Machine has two components.  An infinitely long piece of tape (memory) with re-writable squares and a read/write head whi...

27 Okt 201713min

The Complexity of Learning Neural Networks

The Complexity of Learning Neural Networks

Over the past several years, we have seen many success stories in machine learning brought about by deep learning techniques. While the practical success of deep learning has been phenomenal, the form...

20 Okt 201738min

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