Abstract
In this chapter, we briefly discuss various real-time applications of machine
learning algorithms. Machine Learning Algorithms explain the following topics:
Introduction to ML algorithms, Supervised Learning, Classification, Regression
(Linear Regression, Logistic Regression, Decision Tree, Naive Bayes, Support
Vector Machine, Random Forest, AdaBoost, Gradient-Boosting Trees), and
Unsupervised Learning (K-Means Clustering, Gaussian Mixture Model,
Hierarchical Clustering, Recommender Systems, PCA/T-SNE). Application of
Machine Learning explains various real-time applications like augmentation,
automation, finance, government, healthcare, marketing, traffic alerts, image
recognition, video surveillance, sentiment analysis, product recommendation, online
support using chatbots, Google translate, online video streaming applications, virtual
professional assistants, machine learning usage in social media, stock market signals
using machine learning, auto-driven cars, and real-time dynamic pricing.