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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Avsnitt(605)

Doctor AI

Doctor AI

hen faced with medical issues, would you want to be seen by a human or a machine? In this episode, guest Edward Choi, co-author of the study titled Doctor AI: Predicting Clinical Events via Recurrent ...

23 Juni 201741min

[MINI] Activation Functions

[MINI] Activation Functions

In a neural network, the output value of a neuron is almost always transformed in some way using a function. A trivial choice would be a linear transformation which can only scale the data. However, o...

16 Juni 201714min

MS Build 2017

MS Build 2017

This episode recaps the Microsoft Build Conference.  Kyle recently attended and shares some thoughts on cloud, databases, cognitive services, and artificial intelligence.  The episode includes intervi...

9 Juni 201727min

[MINI] Max-pooling

[MINI] Max-pooling

Max-pooling is a procedure in a neural network which has several benefits. It performs dimensionality reduction by taking a collection of neurons and reducing them to a single value for future layers ...

2 Juni 201712min

Unsupervised Depth Perception

Unsupervised Depth Perception

This episode is an interview with Tinghui Zhou.  In the recent paper "Unsupervised Learning of Depth and Ego-motion from Video", Tinghui and collaborators propose a deep learning architecture which is...

26 Maj 201723min

[MINI] Convolutional Neural Networks

[MINI] Convolutional Neural Networks

CNNs are characterized by their use of a group of neurons typically referred to as a filter or kernel.  In image recognition, this kernel is repeated over the entire image.  In this way, CNNs may achi...

19 Maj 201714min

Multi-Agent Diverse Generative Adversarial Networks

Multi-Agent Diverse Generative Adversarial Networks

Despite the success of GANs in imaging, one of its major drawbacks is the problem of 'mode collapse,' where the generator learns to produce samples with extremely low variety. To address this issue, t...

12 Maj 201729min

[MINI] Generative Adversarial Networks

[MINI] Generative Adversarial Networks

GANs are an unsupervised learning method involving two neural networks iteratively competing. The discriminator is a typical learning system. It attempts to develop the ability to recognize members of...

5 Maj 20179min

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