Introduction to Machine Learning

what is machine learning?

it is the field of study that gives computers a capability to learn without being explicitly programmed e.g. online shopping- amazon observes our searches, clicks, views etc.

it can also be framed as machine adapting to the user based on the data the user generates.

what is the difference between an algorithm and machine learning?

What happens in a typical algorithm is that the computer takes the data and the program as inputs and gives the result as output whereas in machine learning the computer takes the data and previous results as input and generates a better program to process incoming data.

Machine learning explores algorithms that learn/build models from data and these models are then used for different tasks like prediction, decision making or solving problems.

what are the perspectives of machine learning?

the perspective of machine learning involves searching very large space of possible hypothesis(all possible solutions of a problem) to determine one that fits the observed data/ data objects/ data points and any prior knowledge held by the learner.

what are the issues in machine learning?

• what algorithm should be used?

• which algorithm performs best for which types of problems?

• how much training data is sufficient?

• what kind of methods should be used in the process?

• what methods should be used to reduce learning overhead?