{"id":1388,"date":"2019-02-15T10:32:07","date_gmt":"2019-02-15T10:32:07","guid":{"rendered":"http:\/\/kusuaks7\/?p=993"},"modified":"2023-07-28T09:08:50","modified_gmt":"2023-07-28T09:08:50","slug":"the-simplest-explanation-of-machine-learning-youll-ever-read","status":"publish","type":"post","link":"https:\/\/www.experfy.com\/blog\/ai-ml\/the-simplest-explanation-of-machine-learning-youll-ever-read\/","title":{"rendered":"The simplest explanation of machine learning you\u2019ll ever read"},"content":{"rendered":"

Ready to learn Machine Learning? Browse<\/em><\/strong> Machine Learning Training and Certification courses<\/a> developed by industry thought leaders and Experfy in Harvard Innovation Lab.<\/em><\/strong><\/p>\n

You\u2019ve probably heard of machine learning and artificial intelligence, but are you sure you know what they are? If you\u2019re struggling to make sense of them, you\u2019re not alone. There\u2019s a lot of buzz that makes it hard to tell what\u2019s science and what\u2019s science fiction. Starting with the names themselves\u2026<\/p>\n

Machine learning is a thing-labeler, essentially.<\/p><\/blockquote>\n

I\u2019m a\u00a0statistician<\/a>\u00a0and neuroscientist by training, and we statisticians have a reputation for picking the driest, most boring names for things. We like it to do exactly what it says on the tin. You know what we would have named machine learning? The Labelling of Stuff!<\/p>\n

Contrary to popular belief,\u00a0machine learning<\/a>\u00a0is not a magical box of magic, nor is it the reason for $30bn in VC funding. At its core, machine learning is just a\u00a0thing-labeler<\/strong><\/a>, taking your description of something and telling you what label it should get. Which sounds much less interesting than what you read on Hacker News. But would you have gotten excited enough to read about this topic if we\u2019d called it thing-labeling in the first place? Probably not, which goes to show that a bit of marketing and dazzle can be useful for getting this technology the attention it deserves (though not for the reasons you might think).<\/p>\n

It\u2019s phenomenally useful, but not as sci-fi as it\u00a0sounds.<\/p><\/blockquote>\n

What about artificial intelligence (AI)? While the academics argue about the nuances of\u00a0what AI is and isn\u2019t<\/a>, industry is using the term to refer to a particular type of machine learning. In fact, most of the time people just use them interchangeably, and I can live with that. So AI\u2019s also about thing-labeling. Were you expecting robots? Something sci-fi with a mind of its own, something humanoid? Well, today\u2019s AI is not that. But we\u2019re a species that sees human traits in everything. We see faces in toast, bodies in clouds, and if I sew two buttons onto a sock, I might end up talking to it. That sock puppet\u2019s not a person, and neither is AI \u2014 it\u2019s important to keep that in mind. Is that a letdown? Chin up! The real thing is far more useful.<\/p>\n

Let me show you why you should be excited. What do you see in the photo?<\/p>\n

<\/canvas><\/figure>\n

What kind of animal is this? Easy, huh? Now tell me what your brain did with those pixels to get that\u00a0answer.<\/p>\n

You just took in some pretty complex data through your senses and, as if by magic, you labeled it \u2018cat.\u2019 That was so easy for you! How about if we wanted a computer to do the same task, to classify (label) photos as cat\/not-cat?<\/p>\n

Machine learning is a new programming paradigm, a new way of communicating your wishes to a computer.<\/p><\/blockquote>\n

In the traditional programming approach, a programmer would think hard about the pixels and the labels, communicate with the universe, channel inspiration, and finally handcraft a model. A model\u2019s just a fancy word for recipe, or a set of instructions your computer has to follow to turn pixels into labels.<\/p>\n

<\/canvas><\/figure>\n

A model is a recipe that a computer uses to turn data into labels. It\u2019s just some code that the machine uses to convert inputs into outputs, and could be handcrafted by a programmer or learned from data by an algorithm.<\/p>\n

But think about what those instructions would be. What are you actually doing with these pixels? Can you express that? Your brain had the benefit of\u00a0eons of evolution<\/a>\u00a0and now it just works, you don\u2019t even know how does it. That recipe is pretty hard to come up with.<\/p>\n

Explain with examples, not instructions.<\/p><\/blockquote>\n

Wouldn\u2019t it be better if you could just say to the computer, \u201cHere, look at a bunch of examples of cats, look at a bunch of examples of not-cats, and just figure it out yourself\u201d?\u00a0That<\/em>\u00a0is the essence of machine learning. It is a completely different programming paradigm. Now, instead of giving explicit instructions, you program with examples and the machine learning algorithm finds patterns in your data and turns them into those instructions you couldn\u2019t write yourself. No more handcrafting of recipes!<\/p>\n

AI allows you to automate the ineffable.<\/p><\/blockquote>\n

Why is that exciting? This is about expressing our wishes to computers in a way we couldn\u2019t before. We love to get computers to do stuff for us. But how can we possibly give instructions if the instructions are really hard to think up? If they\u2019re ineffable?<\/p>\n

AI and machine learning are about automating the ineffable. They\u2019re about explaining yourself using examples instead of instructions. This unlocks a huge class of tasks that we couldn\u2019t get computers to help us with in the past because we couldn\u2019t express the instructions. Now\u00a0all of these tasks<\/a>\u00a0become possible \u2014 machine learning represents a fundamental leap in human progress. It is the future and the future is here!<\/p>\n

Curious to learn more? Here\u2019s a video where I introduce you to thinking about applied machine learning.<\/p>\n","protected":false},"excerpt":{"rendered":"

You’ve probably heard of machine learning and artificial intelligence, but are you sure you know what they are? If you’re struggling to make sense of them, you’re not alone. There’s a lot of buzz that makes it hard to tell what science is and what’s science fiction. Starting with the names themselves…machine learning is just a thing-labeler, taking your description of something and telling you what label it should get.<\/p>\n","protected":false},"author":335,"featured_media":3238,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"content-type":"","footnotes":""},"categories":[183],"tags":[97],"ppma_author":[2050],"class_list":["post-1388","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ai-ml","tag-artificial-intelligence"],"authors":[{"term_id":2050,"user_id":335,"is_guest":0,"slug":"cassie-kozyrkov","display_name":"Cassie Kozyrkov","avatar_url":"https:\/\/www.experfy.com\/blog\/wp-content\/uploads\/2020\/04\/medium_df35f80d-2bff-4fe3-b741-a94d51320e00-150x150.jpg","user_url":"https:\/\/careers.google.com\/?src=Online\/LinkedIn\/linkedin_profilepage&utm_source","last_name":"Kozyrkov","first_name":"Cassie","job_title":"","description":"Cassie Kozyrkov is Chief Decision Scientist at Google, Inc. With a unique combination of deep technical expertise, and world-class public-speaking skills, she has provided guidance on more than 100 projects and designed Google's analytics program, personally training over 15000 Googlers in statistics, decision-making, and machine learning.\u00a0"}],"_links":{"self":[{"href":"https:\/\/www.experfy.com\/blog\/wp-json\/wp\/v2\/posts\/1388","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.experfy.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.experfy.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.experfy.com\/blog\/wp-json\/wp\/v2\/users\/335"}],"replies":[{"embeddable":true,"href":"https:\/\/www.experfy.com\/blog\/wp-json\/wp\/v2\/comments?post=1388"}],"version-history":[{"count":3,"href":"https:\/\/www.experfy.com\/blog\/wp-json\/wp\/v2\/posts\/1388\/revisions"}],"predecessor-version":[{"id":29735,"href":"https:\/\/www.experfy.com\/blog\/wp-json\/wp\/v2\/posts\/1388\/revisions\/29735"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.experfy.com\/blog\/wp-json\/wp\/v2\/media\/3238"}],"wp:attachment":[{"href":"https:\/\/www.experfy.com\/blog\/wp-json\/wp\/v2\/media?parent=1388"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.experfy.com\/blog\/wp-json\/wp\/v2\/categories?post=1388"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.experfy.com\/blog\/wp-json\/wp\/v2\/tags?post=1388"},{"taxonomy":"author","embeddable":true,"href":"https:\/\/www.experfy.com\/blog\/wp-json\/wp\/v2\/ppma_author?post=1388"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}