ARTIFICIAL INTELLIGENCE

Supervised Learning - Regression & Classification

ARTIFICIAL INTELLIGENCE

MACHINE LEARNING

Machine Learning is a subset of AI technique which use statistical methods to enable machines to improve with experience Machine Learning is further categorized into Supervised Learning, Unsupervised Learning & Reinforcement Learning.

Supervised Learning is where the Data is Pre-categorized or Grouped/labeled, whereas Unsupervised Learning deals with unlabeled data and whereas Reinforcement Learning is an area concerned with how intelligent agents ought to take actions in an environment in order to maximize the notion of cumulative reward.(wiki)

SUPERVISED LEARNING

Supervised Learning shall be majorly of two divided into two types as Regression and Classification

Regression

The Dataset was downloaded from Internet and has been enclosed here for peers to experiment on. The dataset taken for Linear Regression Assignment consists of data related to parameters of Used Cars. The data set contains Used Car Price, Car brands, year of manufacturing, engine volume and km run. based on these available data, using Excel, Matlab & Google Colab the Linear regression is Performed to predict the cost of the used cars and results found to be in-line with each other.

Classification

The Dataset was downloaded from internet and has been enclosed here for peers to experiment on. Have taken couple of problems to experiment & understand the depth of Classification. One of the problem is about probability of survival of horse based on different monitored health parameters and medical conditions. In this example, we have checked couple of Classification method like DecisionTree Classifier & RandomForest Classifier. Further, a problem related to accident data related to people survival, gender of people & station boarded also taken into consideration to perform Logistic Regression also.