
Sign up to save your podcasts
Or


Convolutional neural networks are a machine learning tool that uses layers of convolution and pooling to process and classify inputs. CNNs are useful for identifying objects in images and video. In this episode, we focus on the application of convolutional neural networks to image and video recognition and classification.
Matt Zeiler is the CEO of Clarifai, an API for image and video recognition. Matt takes us through the basics of a convolutional neural network–you don’t need any background in machine learning to understand the content of the episode. He also discusses the subjective aspects of image and video recognition, and some of the tactics Clarifai has explored. This is far from a solved problem.
Matt also discusses the infrastructure of Clarifai–how they use Kubernetes, how models are deployed, and how models are updated.
The post Convolutional Neural Networks with Matt Zeiler appeared first on Software Engineering Daily.
By Machine Learning Archives - Software Engineering Daily4.4
6969 ratings
Convolutional neural networks are a machine learning tool that uses layers of convolution and pooling to process and classify inputs. CNNs are useful for identifying objects in images and video. In this episode, we focus on the application of convolutional neural networks to image and video recognition and classification.
Matt Zeiler is the CEO of Clarifai, an API for image and video recognition. Matt takes us through the basics of a convolutional neural network–you don’t need any background in machine learning to understand the content of the episode. He also discusses the subjective aspects of image and video recognition, and some of the tactics Clarifai has explored. This is far from a solved problem.
Matt also discusses the infrastructure of Clarifai–how they use Kubernetes, how models are deployed, and how models are updated.
The post Convolutional Neural Networks with Matt Zeiler appeared first on Software Engineering Daily.

288 Listeners

1,765 Listeners

476 Listeners

624 Listeners

583 Listeners

300 Listeners

213 Listeners

344 Listeners

776 Listeners

984 Listeners

266 Listeners

213 Listeners

203 Listeners

198 Listeners

228 Listeners