What is Machine Learning?

Machine learning represents the logical extension of simple data retrieval and storage. It is about developing building blocks that make computers learn and behave more intelligently. Machine learning makes it possible to mine historical data and make predictions about future trends. Search engine results, online recommendations, ad targeting, fraud detection, and spam filtering are all examples of what is possible with machine learning. Machine learning is about making data-driven decisions. While instinct might be important, it is difficult to beat empirical data.

What is the use of Machine Learning?

Machine Learning is found in things we use every day such as Internet search engines, email and online music and book recommendation systems. Credit card companies use machine learning to protect against fraud.
Using adaptive technology, computers recognize patterns and anticipate actions. Machine Learning is used  in more complex applications such as:

• Self-parking cars
• Guiding robots
• Airplane navigation systems (manned and unmanned),
• Space exploration
• Medicine

What is Machine Learning best suited for?

Machine Learning is good at replacing labor-intensive decision-making systems that are predicated on hand-coded decision rules or manual analysis. Six types of analysis that Machine Learning is well suited for are:

• classification (predicting the class/group membership of items)
• regression (predicting real-valued attributes)
• clustering (finding natural groupings in data)
• multi-label classification (tagging items with labels)
• recommendation engines (connecting users to items)