Machine Learning is the basis for the most exciting careers in data analysis today. Machine learning brings together computer science and statistics to harness that predictive power. Understanding the philosophy behind machine learning. Machine learning (ML) is a type of artificial intelligence (AI) that allows software applications to become more accurate at predicting outcomes without being explicitly programmed to do so. Machine learning algorithms use historical data as input to predict new output values. Machine learning is the science of getting computers to act without being explicitly programmed. In the past decade, machine learning has given us self-driving cars, practical speech recognition, effective web search, and a vastly improved understanding of the human genome. Machine learning is so pervasive today that you probably use it dozens of times a day without knowing it
The machine learning field is continuously evolving. And along with evolution comes a rise in demand and importance. There is one crucial reason why data scientists need machine learning, and that is: ‘High‑value predictions that can guide better decisions and smart actions in real‑time without human intervention.’
Top-notch professionals in that field who understands how to convey things in technical as well as subject matter experts.
It increases quality and reduces development time due to re-use of previous work, real mapping to the problem domain and modular architecture