Artificial Intelligence-101
Contents
What is AI ............................................................................................................................................ 2
What is learning .................................................................................................................................. 3
Machine Learning................................................................................................................................ 3
Why ML? ............................................................................................................................................. 4
Training and Testing ............................................................................................................................ 4
Phases of ML ....................................................................................................................................... 5
Unsupervised Learning ....................................................................................................................... 6
Reinforcement learning ...................................................................................................................... 7
Designing a learning system ............................................................................................................... 7
Target function.................................................................................................................................... 7
Learning Algorithm ............................................................................................................................. 8
Various target functions ..................................................................................................................... 9
ML Algorithms ..................................................................................................................................... 9
Classification Vs Regression .............................................................................................................. 11
Clustering .......................................................................................................................................... 12
Steps of ML ....................................................................................................................................... 12
ML issues ........................................................................................................................................... 14
Deep learning .................................................................................................................................... 15
How DL learns ................................................................................................................................... 15
Compare Deep learning and ML ....................................................................................................... 16
Biological Neural Network ................................................................................................................ 16
Artificial Neural Network .................................................................................................................. 17
Architecture of Neural Network ....................................................................................................... 18
Single layer .................................................................................................................................... 19
Multilayer ...................................................................................................................................... 19
Recurrent ...................................................................................................................................... 20
Convolutional ................................................................................................................................ 20
DL toolkits ......................................................................................................................................... 21
Where can NN help? ......................................................................................................................... 21
DL usecases ....................................................................................................................................... 22
AI real cases ...................................................................................................................................... 22
Theroy
What is AI
What is learning
Machine Learning
Why ML?
Training and Testing
Phases of ML
Supervised learning
Unsupervised Learning
Re
Reinforcement learning
Designing a learning system
Target function
Learning Algorithm
Various target functions
ML Algorithms
Classification Vs Regression
Clustering
Steps of ML
ML issues
Deep learning
How DL learns
Compare Deep learning and ML
Deep learning requires high end hardware and bigger input dataset
Biological Neural Network
Artificial Neural Network
Architecture of Neural Network
Single layer
Multilayer
Recurrent
Convolutional
DL toolkits
Where can NN help?
DL usecases
AI real cases