This document provides summaries of 3 papers related to deep learning and neural networks: 1. "The 9 Deep Learning Papers You Need To Know About" by Adit Deshpande which summarizes influential deep learning papers. 2. "A Friendly Introduction to Cross-Entropy Loss" by Rob DiPietro which introduces the cross-entropy loss function used in neural networks. 3. "How to implement a neural network Intermezzo 2" by Peter Roelants which explains how to implement a neural network in code.

1. © SuperDataScienceDeep Learning A-Z

2. © SuperDataScienceDeep Learning A-Z

3. © SuperDataScienceDeep Learning A-Z
The 9 Deep Learning Papers
You Need To Know About
(Understanding CNNs Part 3)
Adit Deshpande (2016)
Link:
https://adeshpande3.github.io/adeshpande3.github.io/The-9-Deep-
Learning-Papers-You-Need-To-Know-About.html
Additional Reading:

4. © SuperDataScienceDeep Learning A-Z

5. © SuperDataScienceDeep Learning A-Z
Flattening
Dog
Cat
0.95
0.05

6. © SuperDataScienceDeep Learning A-Z
Flattening
Dog
Cat
z1
z2
0.95
0.05

7. © SuperDataScienceDeep Learning A-Z

8. © SuperDataScienceDeep Learning A-Z
1
0
Dog
Cat
0.9
0.1

9. © SuperDataScienceDeep Learning A-Z
1
0
Dog
Cat
0.9
0.1
Dog
Cat
0.1
0.9
Dog
Cat
0.4
0.6
0
1
1
0
0.6
0.4
0.3
0.7
0.1
0.9

10. © SuperDataScienceDeep Learning A-Z
Row Dog^ Cat^ Dog Cat
#1 0.9 0.1 1 0
#2 0.1 0.9 0 1
#3 0.4 0.6 1 0
Row Dog^ Cat^ Dog Cat
#1 0.6 0.4 1 0
#2 0.3 0.7 0 1
#3 0.1 0.9 1 0
Classification Error
Mean Squared Error
Cross-Entropy
1/3 = 0.33 1/3 = 0.33
0.25 0.71
0.38 1.06

11. © SuperDataScienceDeep Learning A-Z
A Friendly Introduction to Cross-
Entropy Loss
By Rob DiPietro (2016)
Link:
https://rdipietro.github.io/friendly-intro-to-cross-entropy-loss/
Additional Reading:

12. © SuperDataScienceDeep Learning A-Z
How to implement a neural network
Intermezzo 2
By Peter Roelants (2016)
Link:
http://peterroelants.github.io/posts/neural_network_implementation_intermez
zo02/
Additional Reading: