What is Machine Learning?


Artificial Intelligence, also called Machine Learning, is the study of methods that enable computers to learn without being programmed explicitly. The AI technique teaches computers to perform tasks in a similar manner to how humans do it naturally.AI is a process of teaching a computer how to make accurate predictions based on data, without human input. Machine learning allows computers to perform tasks without human input. In the banking, online shopping, and social media industries, machine learning algorithms lead to a smooth, easy and secure experience.


How are Artificial Intelligence and Machine Learning different?



It has two words: “Artificial” And “Intelligence”, which means “a human- made thinking power”. A computer program can simulate human intelligence using artificial intelligence. This system does not need to be pre- programmed, instead, they use such algorithms which can work with their own intelligence.



That allows machines to learn by themselves using data and finally make accurate predictions.


How does Machine Learning work?


The science of machine learning is the process that allows computers to perform without being programmed.  As a result, big data can be analyzed with greater ease. In machine learning, two types of techniques are used: supervised learning that uses known inputs and outputs to develop a model that can predict future outputs, and unsupervised learning, which identifies hidden patterns in data.


Python is a popular language for Machine Learning, so why?


There are many reasons:-


1.     Python is easy to use

2.     Flexibility

3.     Platform independence

4.     Readability

5.     Great Library Ecosystem

6.     Good Visualization  options

7.     Growing popularity

8.     Community support

9.     Low- Entry barrier

10.                        Portable and Extensible


Why is Machine Learning important?


AI can be used to automate tasks previously only available to humans - like customer service calls, bookkeeping, and reviewing resumes. It can also handle complex problems and technical questions that are too big to handle by human experts-think of the detection of images for self-driving cars, the prediction of natural disaster locations and timelines, as well as the identification of potential drug interactions with conditions before clinical trials. That’s why machine learning is important.



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