Machine learning has been a hot topic in recent times. It is being used in a wide range of industries and domains including transportation, logistics, entertainment, finance, entertainment, and many more.

But what is machine learning, and how can you get started with it?

Simply put, machine learning is the process of programming computers so that they can learn from data.

Typically we have to give specific instructions to a computer on how it should process input data to produce some output. In Machine learning, the computer learns how to process the input data to get the desired output 

Let's understand this in detail through an example.

Tom is a 5-year-old boy who does not know the difference between cats and dogs.

We have two stacks of photos, one labelled as dogs and the other as cats.

 We mix the two stacks and then pick one photo and show it to Deep. Then we ask him what is in the picture. He might make a lot of mistakes at the beginning, however eventually he will realize the details of the photo which tell what a cat or dog looks like. For example, he can notice that Cats have a longer tail than Dogs, or they have whiskers that Dogs do not have.

Now replace Tom with a computer in this scenario, and you have machine learning!

The kind of machine learning which we took a look at in the above example is called "supervised machine learning", where you have labelled data that you use to train your machine learning model.

The two other types of machine learning are:

• Unsupervised learning: No labelled data is provided to the neural net
• Reinforcement learning: No data is provided to the neural net; instead the model learns through exploring its environment, if it does the right thing then it gets points, and if it does something wrong then points are deducted, this kind of learning is popularly used in game development.

Now let's talk about how you can get started with machine learning.

One of the prerequisites for machine learning is maths; there are no two ways around it.

With that being said, Maths for machine learning is not as tough as you might think!

The topics which you will have to focus on:

Linear Algebra

• Calculus
• Probability
• Statistics

If you are new to programming in general, then you can get through these topics along with learning python ( we will come back to the languages and tools you will have to learn in a bit ).

The best place to get a feel for these topics in maths is to take a look at the 3blue1brown YouTube channel, which has several video series on all of these topics.

Math is approached visually, which makes it easy for a beginner to digest the concepts.

After which, going more in-depth into these concepts from Khan Academy will help you immensely.

Along with maths, you will also have to learn a programming language; python makes the most sense here as it is easy to get started with.

The Python course on freecodecamp should be sufficient.

I would then recommend you to take the machine learning foundations course by google developers which goes over how one can get started with machine learning in a fun and easy to understand manner.

With this learning path, you can easily get started with machine learning on your own. The sky's the limit here after you have the basics right you can do incredible things with machine learning!

Image by Gordon Johnson from Pixabay