What is Machine Learning? Why You Must Learn It Now

Ever wondered how some things work? Like how you go on YouTube and search for something and afterward that’s all that YouTube shows you? Or how Facebook manages to show you, friends, that you haven’t networked with but you know each other?

All this is made possible through something called machine learning.

What is Machine Learning?

So, what is machine learning? Well, it is a branch of artificial intelligence which in itself, is a branch of computer science. Machine learning entails the ability of a computer to learn things without being explicitly programmed. Imagine the world where you do not have to tell a computer what type of a cat is in front of you but it is able to recognize the cat because it has seen a cat like that before. That’s almost a human-level kind of pattern recognition.

With machine learning, computers are subjected to large data sets from which they learn. They go through the data and are able to pick up patterns. This process is known as teaching and it can be done through two main algorithms which are supervised and unsupervised learning. We won’t go into the nitty-gritty details but these should be the fundamental blocks in getting to know machine learning.

After teaching the computer, the next stage is testing. You have to test the computer so as to a firm that it has indeed learned something. Teaching is normally done by giving the computer a small data set and making it predict what the results are, based on what it already knows.

After testing comes optimizing the algorithm to make sure that it comes with the best possible answer. The cycle is then repeated.

All this may seem like a lot but it’s something interesting and fun and we will give you reasons why you should learn machine learning.

Why Learn Machine Learning?

It’s Then in Thing

Currently, everyone is talking about machine learning, the brains behind businesses and companies are looking to employ as many competent engineers as possible. This should be motivation enough to get you started as you will be assured of getting a spot in the job market.

Learning about machine learning will also keep you at par with the current trends and whenever a conversation sparks up in regards to machine learning, you will be able to contribute without any hesitation.

Did we mention that machine learning engineers earn a pretty penny? Well, they do – a machine learning engineer can from $100,000 upwards per year. For someone who will be solving mental problems through the code, this is a lot as the starting salary for software engineers is $50,000 to $100,000 maximum. This just shows how learning machine learning puts you somewhere in the upper echelon of software engineers.

On top of all this, companies are open sourcing their machine learning libraries. In 2015, Google bought Tensor Flow, a machine learning company that focuses on deep learning and open-sourced all their code so that people can work on it am improve on it. This helps in progressing the technology much faster. Apart from that, companies also hold machine learning competitions every now and then as means of improving their technology or getting the best minds to work for them. For example, Google holds competitions on Kaggle as a way of recruiting engineers.

Other companies also have a stake in this industry. Netflix, in 2006, issued a $1 million prize for anyone who could improve their recommendation algorithm by 10%. Olx, a few weeks back, also held a competition on Hackerrank as a way of recruiting machine learning engineers. There is so much going on in this space!

It’s Linked to Data Science

As a machine learning engineer, you will be forced to wear two hats at once, one is for data science and the other is for machine learning. For those who do not know what data science is, it is defined as a way of extracting meaningful information from data whether the data is structured or unstructured, it is also known as data mining.

When you’re competent in both of these fields, you become a hot commodity as it means that you can go through tons of data, extract what is valuable and make sense out of it, and later use that information to train a computer to predict the results.

Furthermore, data science was voted as the sexiest job of the 21st century, I mean what more could you ask for? The salary for a data scientist is also good ranging from $110k per year and companies are recruiting like crazy. Apple bought a company in 2017 for $200 million that focuses on dark data. Sounds scary right? Well, it’s not, dark data is basically the files that form the basic structure of a file system and store all the unused information. This acquisition, it shows that companies are looking to make sense of what people do. Google uses data science to determine our behaviors thus improving our search results or notifying us whenever something that may appear interesting to us occurs, all this is because of machine learning and data science.

With data science, you help in solving the big questions such as what is beyond the blue skies? Through the help of satellites, we can gather information and query it using data science and come up with answers to questions of whether there are aliens or not. Data science, combined with machine learning, also assists in improving health care. Google’s Tensor Flow has helped in detecting the rarest form of eye cancer that leads to blindness.

Be Wary Of the Dangers of A.I

(Source: https://www.pexels.com/photo/flight-technology-tools-astronaut-39644/)

A lot has been said concerning the dangers of A.I. If you have watched the Hollywood blockbuster movie the Terminator, then you could possibly be scared if such a machine came to life. With such looming dangers, we need to be cautious of what we build and that’s why there is a need for us to learn about artificial intelligence so as to protect ourselves.

Recently, Facebook had to shut down its own A.I after it created its own language that humans cannot understand. This goes to show that we may not be able to control the A.Is that we build. Elon Musk warned that A. I’s could be dangerous and a regulating body should be formed so as to check the use of AI. All this should not mean that A.I’ cannot do good things.