The Latest buzzword floating around is Machine Learning. What is machine learning? Why do we need Machine learning?
Whenever we hear machine learning, we think of some sort of robot who is getting us to an apocalypse or a computer nerd, who uses a whole lot of math. But in reality, machine learning is not so complicated, and anyone can use it to create some of the most amazing programs
Most of the coding done is a task. You write some code, then fix the bugs, then write some more code, then fix the new code, and then, finally, you have written the correct code. However, In machine learning, the underlying algorithm is selected or designed by a human, and the algorithms learn from the data, rather than direct human intervention, about the parameters that will shape a model for making predictions. In another way, a data set is used to train a mathematical model so that when it sees a sample input, it knows what result we want. Models typically take data as an input and then output a prediction of something of interest.
Let’s use a simple example to understand.
Problem: finding if a number is divisible by 2
When we are coding: the program will be to take an input, divide the number by 2 if the number is an integer, then the number is divisible, else it’s not
In machine learning: we will have to give the computer a dataset of numbers, preferably from -5000 to 5000, and have a second column, and store that if the number Is divisible by 2, we have a 1, and if it is not then the number is 0.
Then this data will be read and then the computer will come out with an equation, where we can input a Value, we want and then it will give us a value, between 1 and 0, to tell us if the number is divisible or not.
To create amazing programs, you don’t need to be a Machine Learning Expert. A little knowledge and an inquisitive spirit can go a long way. When you start to understand how the machine learning programs work, and the underlying algorithms, you can also go on to create programs that do wonders. In this series, We will discuss through some theory and throughout this series, you will code a lot of machine learning programs, some big, some small, but all will give you a whole lot of experience, so you can say, I am a Machine Learning Enthusiast