{"id":2439,"date":"2019-02-11T10:00:53","date_gmt":"2019-02-11T10:00:53","guid":{"rendered":"https:\/\/devbloglavaprotocols.nityo.in\/all-you-need-to-know-about-machine-learning\/"},"modified":"2019-02-11T10:00:53","modified_gmt":"2019-02-11T10:00:53","slug":"all-you-need-to-know-about-machine-learning","status":"publish","type":"post","link":"https:\/\/www.lavaprotocols.com\/the-cloud-blog\/all-you-need-to-know-about-machine-learning\/","title":{"rendered":"All You Need To Know About Machine Learning"},"content":{"rendered":"
<\/div>

By Aishath Nashwa, Business Analyst, and Prethiba Esvary, Marketing and Communications Executive, Lava Protocols<\/i><\/strong><\/p>\n

<\/p>\n

If you went onto Google and typed out \u2018Machine Learning\u2019, you\u2019d see scores of articles about this topic. But for some of us, these articles can appear complicated, especially if we\u2019re not tech junkies or don\u2019t work in the IT sector. <\/span><\/p>\n

You may not realise this but our lives today are very much dependent on devices which use machine learning. So, having a conversation with a tech junkie even though you\u2019re not a techy person yourself shouldn\u2019t be a problem. ?<\/span><\/p>\n

We\u2019ve drilled down the basics of machine learning into 5 points. Enjoy reading!<\/span><\/p>\n

\"\"<\/p>\n

\u00a0<\/p>\n

1. What Is It, Really?<\/span><\/strong><\/h2>\n

In technical terms, machine learning involves algorithms and data and numbers. To break it down for you, machine learning involves learning from examples and experiences rather than being programmed. With more experience, it gets smarter and better. <\/span><\/p>\n

Take a baby as an example. How do we teach them the alphabet, numbers, and how to recognise various objects and colours? Through repeated exposure of the object, and in different variations, until they are able to identify the characteristics unique to that object. Through experience, the baby will eventually learn to distinguish between say an apple and an orange. <\/span><\/p>\n

Similarly, you will need to feed a machine with various images of an apple and an orange, for the machine to be able to identify characteristics unique to an apple and orange. The more varieties of apple and orange images it is fed, the better it gets at telling the two apart.<\/span><\/p>\n

\u00a0<\/p>\n

2. What Are Some Real- Life Examples?<\/span><\/strong><\/h2>\n