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.