📜 In short (TLDR)

Train the machine to predict future results based on past data.

⛳ The longer story

Machine learning is the process of rebuilding the human decision-making ability using machines.

As humans, we take decisions based on our past experiences.

But machines, machine doesn’t have the sixth sense to collect and analyze past experiences themselves.

So we train machines to find hidden patterns in data. Based on that pattern the machine will take knowledgeable guesses.

For that, we need to convey our problems in a way that machines can understand.

(machine only understands numbers)

❓Why do we bother about machine learning now?

• Huge data is generated day by day

  It’s too complex to handle with traditional approaches

• Advancement of computation resources

  With the help of hardware and software resources,

  processing speed,

  accuracy,

  are high compared to traditional ways

🤖 Examples of machine learning applications

• Personal assistants (google assistant, siri).

• Pair programming with code snippet generation (copilot, tabnine).

• Chatbots engage with customers in a human-friendly way.

• Youtube/Netflix recommendations based on your interests.

• Categorize the customers based on their past behaviors.

📝 Summary

In this blog we went through what is machine learning, why do we use it, and a few examples of machine learning systems that we come across in daily life.

Machine learning most emerging technology nowadays.

If you are interested to learn more about machine learning online for free, check my previous blog here.

Happy exploring! 😇