Learn the basic terminologies of Machine Learning from Alphabets!

When we first went to school the basic thing we learnt were the alphabets. Then we were thought to pronounce the alphabets, write them in capitals and cursive. This was done as a rigorous process of learning for many days. As a result after a few days we were able to correctly identify the alphabets, pronounce them and even write them both in Capitals as well as in Cursive.

Some of the basic terminologies of Machine Learning are:

1. Accuracy
2. Algorithm
3. Dataset
4. Model
5. Training
6. Testing

Relating these terminologies to Alphabets:

The alphabets were shown to us in various forms through videos, images, writings in the black board and a lot more. The Alphabets is referred to as Dataset. The way our teacher teaches us can be compared to Algorithm. The way we try to learn the alphabets can be compared to Training. Our brain stores what our teacher teaches using various methods. Our brain is compared to the Model. The small class tests which has some portion of what the teacher taught us is referred to as Testing. The marks we get in the small tests can be compared to Accuracy.

Now we know some of the basic terminologies of Machine Learning. The next article is about Simple Linear Regression.