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1
Intro
2
Electricity
3
Deep Learning
4
Getting Started
5
Theres no free lunch
6
Deep Learning in 3 Steps
7
What is Deep Learning
8
Artificial Neural Networks
9
Computer Vision
10
Speech Recognition
11
Machine Translation
12
What do these examples have in common
13
Overlaying the examples
14
Generic functions
15
Models
16
Classifiers
17
Tensors
18
Tensor Models
19
Artificial Neuron
20
Architecture
21
Machine Learning
22
Training Data Examples
23
How Does Training Work
24
First Step
25
Forward Pass
26
BackPropagation
27
Gradient Descent
28
Why Deep Learning Works
29
Composition
30
Narrow Intelligence
31
Conclusion
32
Why Scala
33
Type Safety
34
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
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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.

Dive into Deep Learning with Scala

Scala Days Conferences
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