Revolutionizing the Future with Machine Learning

Introduction: Machine learning is self learning from the experience gained. It is a branch of artificial intelligence. Algorithms and statistical models identify patterns and predict.

Quoting Arthur Samuel famous: "Machine learning is the study of how to construct programs that automatically improve with experience".

How Machine Learning Works:
The training of a learning model consists of several inputs from different kinds of datasets and algorithms. This makes it possible for such models to recognize patterns and to make decisions based on the discovered associations. The three types of machine learning learning.

Supervised Learning:

Label data-driven training of the model.
Unsupervised learning:

Patterns are found in unlabeled data.
Reinforcement Learning:

Learn by trial and error with rewards and penalties.

Application Areas of Machine Learning:
These include:

Health-care: Disease prediction, personalized treatment.

Finance: Fraud detection, algorithmic trading.

Transport: Autonomous vehicles with traffic predictions.