Introduction to Machine Learning


What is Machine learning?

How do humans differentiate between and orange and a banana? It’s simple, right! The orange is orange in colour while banana yellow. As a child, this was the most basic difference we were taught. But soon we started to learn other difference as well, like the shape. This does not happen in a single chance. We are repeatedly shown these fruits and hence we learn to distinguish them.

Now, let’s see how we relate this to machines.

Now, a machine cannot see like a human, but it wants to learn to distinguish between the orange and the banana. What do we do? We give it various inputs in the form of shape, size and colour so that the two fruits can be distinguished. These inputs are learnt by the machine and then it is able to identify the fruit when an unknown combination of shape, size and colour is given.

This process in which machine learns from a set of inputs and applies it to predict a new outcome is machine learning.

Machine Learning, Data Mining, Data Science, these are a few very common terms one comes across nowadays as a computer science student. Before diving machine learning let’s see what these terms mean.

Machine Learning is the application of various algorithms that automate the process of iterating through the data and help computers to derive useful insights without explicitly programming what to look for in the data.It basically involves parsing the data, learning from it and deriving an inference or prediction based on the data.

Data Mining, in its simplest form, is said to be the process of analysing data and summarising the results. It deals with identifying the patterns and correlations within the data.

Data Science is an interdisciplinary field dealing with data engineering, visualisation, statistics, and advanced computing. Data Science engineering skills like database set up, integrating database and applications, data cleaning and pre-processing and analytical skills varying from the use of a simple statistical formula to complicated machine learning algorithms to understand the patterns in data.

Here, we will mainly be focusing on machine learning and its algorithms.