Introduction to AutoML

Introduction to AutoML

How often do we grow our thinking and general intelligence when exposed to new ideas and ways of doing things? Welcome to the world of AI and machine learning.

What is Machine Learning

Machine learning is an application of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed.

with traditional programming (well the one most of us do). We give computers a set of inputs and rules to perform on the inputs and the computer gives us the output.

for instance below is a code snippet that calculates the sum of two numbers.

double calculate(double a, double b){
  return a + b; 
}

How different is writing code for ML? with machine learning we always have the inputs and the expected output so the problem here is determine the set of rules that once passed to the inputs will lead us to the expected output.

example

One method of ML that is commonly used
For instance you are writing a food image recognition software. here you give the computer all the food images that you can have access to, the computer then studies these images and deduce 'common characteristics' such that when any other image is given to it it can tell weather it is food or not food.

Automated Machine Learning

The high degree of automation in AutoML allows non-experts to make use of machine learning models and techniques without requiring to become an expert in the field first.

What Do I mean?
ML is fairly expensive and demanding field to explore. So large companies like (google , facebook , microsoft , amazon ...) that have the resources and experts that can build and run these ML workloads usually share part of whatever they have already built to the general public as a paid service.
Some of these products include

  1. Firebase ML kit - This is a powerful mobile sdk that android / ios developers can leverage in order to build ML enabled mobile apps at google scale without having ML expertise.

2.Aws sage maker- This is a fully managed service that provides every developer and data scientist with the ability to build, train, and deploy machine learning models quickly.

  1. Facebook AI - facebook has alot of contributions in all the various levels of AI abstractions . some of its products that fit into this space include (FastText, Translate, ParlAI, Fairseq )

The Future of AI

AI is projected to lead the next round of industrial revolution, and with more data being generated yearly and computing power especially in the mobile and embeded devices , more application developers will be required to have some sort of AI in their applications and this will even lead to rise in the automated ML platforms.

As a developer , being equiped with the AI concepts and having the ability to run some workloads in the Automated platforms can be a great boost to your career.

Cheers lets explore more ...