“Machine Learning in Layman’s Language”

Now, In 21st Century Machine Learning and Artificial Intelligence are going to play a major role. We are producing a large amount of data every day, Data of Consumer shopping patterns at E-commerce sites and Grocery stores, Corporates company’s sales data, etc.

We require to apply Machine Learning to get the insights from this Data. So the Trend of Machine Learning is going high. But the what is Machine Learning? Is it new from the traditional way of programming? Here, Let’s see in Layman’s Language:

The Traditional Computer Programming:

In the traditional way of computer programming, We are giving inputs to the computer and after the process, the computer generates the output.

The Tradition Way of Computer Programming

For an Example:

Example of The Tradition Way of Computer Programming

Here, We are giving input x=10 and y=5 to the computer and it generates the output as z=15.

Machine Learning:

But, Here is the catch in Machine Learning, The objective of Machine Learning is to get insights from the data, here the data is already generated. From which, we select input and output (Target). So, In Machine Learning, We are giving input and output together to the computer and the computer generates output as a program.

Machine Learning

For an Example:

Example of Machine Learning

Here, we are giving input x=10,y=5, and output z=15 And the Machine Learning algorithm generates the program x + y = z.

So, Machine Learning is nothing but it generates the relation between the input and the output. Machine Learning Algorithm automatically learns from inputs and output and provides the output as a program.

After getting this relation(program) we can predict the output of the unseen inputs. It is helpful in case of forecasting the future sales of the organization. where we already past data of sales and its affecting variables. After we taking sales affecting variables as input and sales as output(Target), we provide it to the machine learning algorithm it generates the relation. From which we can predict and forecast future sales.

In real-world machine learning, The data is huge, which contains millions of rows and hundreds of columns. Machine learning algorithm generates the relationship between this huge dataset and establishes the machine learning model to predict the outputs.

Crux :

“We Human learns from experience and reacts according to it. But Machine (Computer) learns from the data we provide to it. From this data it generates the data model from which it predicts the output of unseen inputs.”

Applications of Machine Learning:

1. Prediction
2. Image recognition.
3. Speech recognition.
4. Product recommendations.
5. Email Spam Filtering.
6. Stock price prediction.

Thank you for reading my first blog on Machine Learning. I have tried my best to explain Machine Learning in the easiest manner. I want to contribute to the Data Science Community by sharing knowledge of this amazing field in the layman’s language.

You can reach me out on my Linkedin: www.linkedin.com/in/saurabh2829