Supervised Machine Learning - Classification Algorithms

Course: 365datascience - Supervised Machine Learning Bootcamp

Supervised learning: is a type of machine learning in which machine learn from known datasets (set of training examples), and then predict the output. A supervised learning agent needs to find out the function that matches a given sample set. Supervised learning further can be classified into two categories of algorithms:

1. Regression : When the outcome is pure numeric value. eg : Home price prediction. You are trying to estimate value of price.

2. Classification : When the outcome is a category/class. eg: Fraud detection. You are trying to identify Yes/No class

However in this repository we will be focusing solely on the following classification algorithms:

Algorithms	Notebooks	Datasets
Naïve Bayes	MultinomialNB	Youtube Spam Collection
K-Nearest Neighbors	K-NN Grid Search CV	Synthetic Data
Logistic Regression
Decision Tree - Random Forests	Decision Tree , RF - Glass Identification, RF - Census Income	Iris Flower , Glass Identification , Census Income
Support Vector Machines	SVM	Mushroom
Ensemble - Xgboost	Xgboost	IBM Telco Customer Churn