What is Neural Network? | Example of Categorical Response at Two Levels with R

Provides steps for applying artificial neural networks to do classification and prediction.
R & Data files: https://github.com/bkrai/R-files-from...
Machine Learning videos: https://goo.gl/WHHqWP
Timestamps:
00:00 Neural Networks in R
00:05 Data, input, hidden, and output layers
01:46 Min - Max Normalization
03:34 Data Partition
04:30 Neural Network Model
07:10 Prediction
08:53 Node Output Calculation with Sigmoid Activation Function
12:04 Confusion Matrix and Misclassification Error
15:32 More Neurons in Hidden Layer
17:05 Neural Network with Two Hidden Layers
18:33 Neural Network Repeat Calculations
22:41 Neural Network Advantage
22:47 Neural Network Disadvantage

neural network is an important tool related to analyzing big data or working in data science field. Apple has reported using neural networks for face recognition in iPhone X.
Machine Learning videos: https://goo.gl/WHHqWP
Becoming Data Scientist: https://goo.gl/JWyyQc
Introductory R Videos: https://goo.gl/NZ55SJ
Deep Learning with TensorFlow: https://goo.gl/5VtSuC
Image Analysis & Classification: https://goo.gl/Md3fMi
Text mining: https://goo.gl/7FJGmd
Data Visualization: https://goo.gl/Q7Q2A8
Playlist: https://goo.gl/iwbhnE
R is a free software environment for statistical computing and graphics, and is widely used by both academia and industry. R software works on both Windows and Mac-OS. It was ranked no. 1 in a KDnuggets poll on top languages for analytics, data mining, and data science. RStudio is a user friendly environment for R that has become popular.