Dineshkumar Ponnusamy

The actual piece of work can be written in a line of one or two (that's the reason we choose python). Before even debating whether theory takes priority or practical takes priority, lets focus on why we need machine learning?

People tend to write programs for everything they want computer to take care of. In technical world, this process is called automation. Anything that can be automated can be automated in IT industry. But there comes a situation, when it cannot be automated.

For example, If I give you a picture of cat and picture of dog, how do you differentiate both of them?

In order to identify the difference, you will ask lot of questions about its characteristics.

1. How big it is?

2. How is the skin?

3. Does it have legs?

4. How many legs does it have?

Can we answer with these 4 questions, the answer is NO. We need more details and we need to learn from the previous answers. Even if it is technically possible to write all the possible questions and come to conclusion, but all the efforts will be wasted if I put another picture of Mouse, and ask you to choose, what is Cat, what is Dog and what is Mouse. The problem is choosing the feasible way to teach machines to understand our thinking behavior based on previous analysis.

How a child learns?

The kids learn based on watching, listening, thinking and then uses the same pattern to analyze things. The same way, we are training the systems, we are providing guidance using algorithms to get the best output, cross verifying the results, and providing the feedback to the system. In that way, the machine increases it learns. I believe that now you might have understood, the process of making the computer to learn and think based on learning is Machine Learning.

In real world, Self Driving Cars, Personal Assistants (Alexa, Google, Cortana, Siri), Product recommendations (Amazon you might be interested in, Netflix recommended for you), Search Engine results refining (How google sends results and advertisements), Chat bots (If you message any company support, it will answer based on its learning experience), and many more. Will see one by one in detail later.

Well, the best way to learn machine learning is doing it in parallel and put more focus on the concepts. Because, once you are aware of the concepts you can implement it in any programming language you want.