AI
This chapter works through Machine Learning, the anchor topic behind Machine Learning.
Machine Learning is a subfield of Artificial intelligence
Artificial Intelligence suggest that machines can mimic humans in:
Programming languages involved in Machine Learning and Artificial Intelligence are:
Traditionally, Machine Learning applications are using R or Python.
Machine Learning often uses line graphs to show relationships.
- Data Collections - Scatter Plots - Graphs
A Perceptron is an Artificial Neuron .
Neural Networks are used in applications like Facial Recognition.
A Perceptron must be Tested and Evaluated .
An ML model is Trained by Looping over data multiple times.
- Relationships - Labels - Features
Up to 80% of a Machine Learning project is about Collecting Data :
- Clusters are collections of similar data - Clustering is a type of unsupervised learning - The Correlation Coefficient describes the strength of a relationship.
A Regression is a method to determine the relationship between one variable ( y ) and other variables ( x ).
The deep learning revolution started around 2010.
Brain.js is a JavaScript library that makes it easy to understand Neural Networks because it hides the complexity of the mathematics.