Project 1

Q1) Supervised learning is a type of machine learning algorithm that learns from a set of training data that has been labeled training data.

Common algorithms and techniques in supervised learning include Neutral Networking, Support Vector Machine, Logistic Regression, Random Forest.

Unsupervised learning is a type of machine learning algorithm that doesn’t require any training data with labels.

Examples of unsupervised methods include algorithms such as K-means clustering, Principal Component Analysis, Hierarchical clustering, or Semantic clustering.