A Beginner’s Guide to Machine Learning – Let’s teach the computers.

Before we jump, into this world. Let’s think:-

What is Human Learning?

Brain learning, is the process by which individuals acquire new knowledge, skills, behaviors, or attitudes through experiences, ( mistakes we make in the past ) study, practice, and exposure to information.

Simple & Easy Peasy – No Trick here.

But now think about Speed & Adaptability to new changes our minds can have.

“When new things happen in our life the mind takes time and sometimes it’s difficult to adapt to the new changes to our life especially when it’s something we don’t expect such as any disease, Job Loss, or any other changes which we are not prepared for.

Although with time everything became Hakuna Matata one day“

Lastly, think about the information we can store in our brains.

That’s where Machine learning is super powerful in remembering things and storing the data and adaptability to new changes and that’s why it is called Machine learning because machines do not have emotions.

Let’s go:-

What is Machine Learning?

Its – “Teaching computers”  from patterns observed from data.  – Simple as that

Machine Learning & Human learning have one thing in common they both get matured ( accurate ) with more life experiences or historical data.

Shakespeare said…

“Wisdom comes with age & experiences in Humans”

In simple terms, more the life experiences or examples we have the more we are supposed to be wise.

In the case of machines, wisdom ( Accuracy ) will come with more historical data we expose to our algorithms.

“In the Data Science world, a machine’s decision-making capability becomes more robust with the data volume”

Surely, we have as many applications as you can think of, but let me drill down in simpler words.

Let’s see with an example,

Predict Salary for Eric?

That’s what we call Regression algorithms ( predicting a continuous value ).

Let’s see another example,

Predict Default – Yes or No ( 0/1 )  for Eric?

That’s what we call Classification algorithms ( predicting a 0 or 1 ).

Key Takeaways:-

• Machine Learning – Teaching computers from the data.
• We require Machine Learning because they learn by themselves with ease, speed, and adaptability to new changes.
• “Computer algorithms that improve automatically through experience”