In this deeplizard episode, learn how to prepare and process our own custom data set of sign language digits, which will be used to train our fine-tuned MobileNet model in a future episode.

VIDEO SECTIONS

  • 00:00 Welcome to DEEPLIZARD – Go to deeplizard.com for learning resources
  • 00:40 Obtain the Data
  • 01:30 Organize the Data
  • 09:42 Process the Data
  • 13:11 Collective Intelligence and the DEEPLIZARD HIVEMIND

Everyone loves Keras and here’s a great article on why that is.

Today, the Deep Learning ecosystem is much more mature, so thankfully one can get by with learning fewer frameworks. While many excellent frameworks have been released over these intervening years, and are being used in specialized niches, the major ones are Keras, Tensorflow, and Pytorch. Pytorch became popular because of its eager execution model, which Tensorflow did not allow, and which Keras hid behind its cleverly-designed API. Keras has since been subsumed into Tensorflow as tf.keras, but the original Keras lives on as well, with an additional CNTK (from Microsoft) backend. For its part, Tensorflow, in its 2.x incarnation, has embraced Pytorch’s eager execution model, and made tf.keras its default API.

deeplizard  introduces MobileNets, a class of light weight deep convolutional neural networks that are vastly smaller in size and faster in performance than many other popular models.

VIDEO SECTIONS

  • 00:00 Welcome to DEEPLIZARD – Go to deeplizard.com for learning resources
  • 00:17 Intro to MobileNets
  • 02:56 Accessing MobileNet with Keras
  • 07:25 Getting Predictions from MobileNet
  • 13:32 Collective Intelligence and the DEEPLIZARD HIVEMIND

In this video, Mandy from deeplizard  demonstrates how to use the fine-tuned VGG16 Keras model that we trained in the last episode to predict on images of cats and dogs in our test set.

Index:

  • 00:00 Welcome to DEEPLIZARD – Go to deeplizard.com for learning resources
  • 00:17 Predict with a Fine-tuned Model
  • 05:40 Plot Predictions With A Confusion Matrix
  • 05:16 Collective Intelligence and the DEEPLIZARD HIVEMIND