Introduction to Machine Learning
Machine Learning (ML) is one of the most transformative technologies of the
modern era, empowering systems to learn and improve from experience without
being explicitly programmed. It lies at the core of Artificial Intelligence (AI) and is
the driving force behind advancements in diverse fields such as healthcare,
finance, entertainment, and more.
What is Machine Learning?
Machine Learning is a subset of AI that enables machines to identify patterns,
make decisions, and predict outcomes based on data. Instead of relying on
hardcoded rules, ML algorithms allow computers to improve their performance as
they process more data.
Key Characteristics:
Focuses on data-driven learning.
Adaptive systems that evolve over time.
Reduces the need for manual programming.
Example:
When Netflix recommends shows or Amazon suggests products, they are
leveraging ML algorithms that analyze your preferences and predict your
interests.
Historical Context of Machine Learning
The roots of ML can be traced back to the mid-20th century when researchers
started exploring ways to teach computers to perform tasks without explicit
instructions.
1950s: Alan Turing introduced the concept of machine learning with his
question, "Can machines think?"
Machine Learning (ML) is one of the most transformative technologies of the
modern era, empowering systems to learn and improve from experience without
being explicitly programmed. It lies at the core of Artificial Intelligence (AI) and is
the driving force behind advancements in diverse fields such as healthcare,
finance, entertainment, and more.
What is Machine Learning?
Machine Learning is a subset of AI that enables machines to identify patterns,
make decisions, and predict outcomes based on data. Instead of relying on
hardcoded rules, ML algorithms allow computers to improve their performance as
they process more data.
Key Characteristics:
Focuses on data-driven learning.
Adaptive systems that evolve over time.
Reduces the need for manual programming.
Example:
When Netflix recommends shows or Amazon suggests products, they are
leveraging ML algorithms that analyze your preferences and predict your
interests.
Historical Context of Machine Learning
The roots of ML can be traced back to the mid-20th century when researchers
started exploring ways to teach computers to perform tasks without explicit
instructions.
1950s: Alan Turing introduced the concept of machine learning with his
question, "Can machines think?"
