The most asked question from Machine Learning Fans is -- What should be my first step towards learning this huge branch of Artificial Intelligence.

So the answer to this quite simple question is Time and Curiosity. Ask yourselves, do you have what it takes.

You must be interested and eager to learn. That's why you must have clicked on this Article.

First of all the usual thing - Let's define What is Machine Learning?

Machine learning is a branch of artificial intelligence (AI) and computer science that focuses on using data and algorithms to imitate the way that humans learn, gradually improving its accuracy.

This Definition was taken from IBM So, the thing is this is not that much important. (Of course, it is slightly important if you are a total newbie.)

Now, let's define Machine Learning in FriedMind's Way: Let's break these two words -

Machine- the machine here refers to our Computer, it could be a laptop, mobile, etc. A computer is a digital electronic machine that can be programmed to carry out sequences of arithmetic or logical operations (computation) automatically.

Learning - Let's see what Wikipedia has for us - > Learning is the process of acquiring new understanding, knowledge, behaviors, skills, values, attitudes, and preferences. The ability to learn is possessed by humans, animals, and some machines;

Quite interesting, right? --machines can learn, how? They are not Living things. then how do they learn.

That's where the magic of Mathematics happens ;)

Let's not deep dive into mathematics. To learn more about the maths behind ML refer to this

Steps for how humans learn machine learning to make a machine learn:-

Step 1: Of course Adjust your Mindset. Get yourselves buckled up for this new Skillset.

Step 2: Learn Various ML Concepts - Learn Terminologies of Machine Learning, Types of Machine Learning

Step 3: Understand the Prerequisites - Learn Linear Algebra and Statistics.

Step 4: Learn Python because it is currently the most popular language for ML.

Step 5 : Learn different Python Libraries - pandas, numpy, matplotlib and the most important for newbies is scikit-learn.

Step 6: Practice starter concepts like data collection, integration, cleaning, and preprocessing using above listed libraries.

Step 7: Learn various models and practice on real datasets.

Step 8: Now you are ready to rock in this journey.

Hope you guys liked my first ARTICLE. Feel Free to drop suggestions, Thank you.

Quote for this Article

"Everything is Easy if you are crazy. Nothing will be easy if you are lazy"