What features should a deep learning library provide
35
Three deep learning libraries
36
Example code
37
Business problem
38
Look for Existing Solutions
39
Supervised Learning
40
Data Source
41
Architectures
42
Convolutional
43
Neural Network
44
Model Building
45
Training
46
Training with more neurons
47
convolutional layer
48
network classifier
49
run model
50
deployment
51
main takeaways
Description:
Explore deep learning concepts and their implementation in Scala in this conference talk from Scala Days Berlin 2018. Learn about artificial neural networks, computer vision, speech recognition, and machine translation. Understand the fundamentals of deep learning, including tensors, models, classifiers, and the training process involving forward pass, backpropagation, and gradient descent. Discover why deep learning works through composition and narrow intelligence. Examine the benefits of using Scala for deep learning, such as type safety, and compare three deep learning libraries. Follow along with example code to solve a business problem using supervised learning, convolutional neural networks, and model deployment. Gain practical insights into building, training, and deploying deep learning models with Scala.