The world is becoming smart, smarter than ever before. There are homes that know how to turn on the lights by judging its intensity and there are cars that can drive themselves. Isn’t it something like living in a sci-fi world? Everything that was imagined is turning into reality. Among all that we hear about the upcoming technology, machine learning (ML) is a common term being associated with almost all of them. The term has been more misinterpreted than understood and there has been a considerable measure of hype buzzing around it.
With more gadgets and technologies being launched every day, customers are keen to know what is it that is making them smarter? They are curious to discern the tech running behind the smartness and understand how it can benefit them in their personal as well as business ventures. This inquisitiveness towards the “working” has lured people to read and question about the same, however, the responses have not been palatable. For instance, you may often see mobile companies using the terms artificial intelligence and machine learning interchangeably for their products, now this is how a misperception is shaped. The customers do not understand the difference between the two and start treating them as synonymous to each other.
The aim here is to make you understand the similarities and differences between “machine learning” and the terms it is confused with. this write up shall provide you a clear insight so that you can differentiate between the hype and the reality. It is important because, machine learning forms an integral part of almost all the data-driven work.. In the event that you intend to consolidate it into your business, you should discern what it may or may not be able to do for you. Having a clear perspective will ensure that you develop a strategy that fits into your business module and help you accomplish the set objectives.
Removing the Misconception
You know how they say in school that if your basics are clear, you will understand each and every concept and if not then surely there will be trouble. This concept will hold true in your entire life and therefore, if you recognize the simple notion of machine learning you’ll never be influenced by the related hysterias. The figure below describes machine learning it its naivest form.
There is a lot of reality and there is a lot of hype pertaining to machine learning. But with the above illustrated diagram it should be clear that machine learning is, training a machine by giving it a large amount of data and then letting it perform based on that learning.
Exposing the Myths
Machine learning is currently going through a phase of inflated expectations. There are a lot of organizations looking forward to conceptualize and run ML projects without even exploring the power of basic analytics. How do you expect them to meet their goals when they do not know what ML can or cannot do? In such a scenario it becomes imperative to know the myths and truths related to the subject.
#1 Machine Learning and Artificial Intelligence are same
One of the commonest misconception is between artificial intelligence and machine learning. Both the terms are not only different in words but are two different fields belonging to a bigger pool of data science. In order to understand the difference consider this example – You wish that the camera of your phone should recognize a dog. Now in order to do that you provide it with a huge amount of data that contains pictures of all the types of dogs present in the world. With the help of these images the camera is able to create a pattern that resembles a dog. Now whenever you point the camera towards the dog, it matches the pattern and that is how you get a positive hit. On the other hand, pointing the camera towards a cat doesn’t identify it as anything. This is a machine learning process where the machine is being trained to accomplish a particular task. Artificial Intelligence on the other hand is a broader concept, here the machines are trained in such a way that they can make their own decisions just like human brain. If you put a cat in front of a camera that works on an AI technology, it will use it as another input and further reuse it to train itself. This training would help the AI enabled phone to tell that is isn’t a dog but it may be something else that can be explored.
#2 Hiring the best ML talent is sufficient to resolve business issues.
Business firms are spending a lot of money in gathering the best machine learning talent which can analyse their data and offer useful insights. What they forget in the process is that machine learning is just one part of an effective strategy, the basics is to have the right type and amount of data. If there is no one who can fetch the data, what will the professionals work upon? Therefore, businesses do not need a staff good in one field but someone who knows how to work from the scratch. There are data science firms all over the globe that can help business develop a correct approach and provide the useful insights they have been looking for.
#3 ML implementation requires humongous infrastructure.
Years before it was said that if you wish to carry our ML operations in your premises, you’ll need to invest a large amount in infrastructure. The scenarios have changed now. Since data science has become such an integral part of the business world, there are professionals who are teaming up to form organizations that work purely on data and offer all the insights you want. Isn’t that easier to just let the experts handle all the work? This not only allows a business owner to explore the problem that needs to be solved but also saves time that he/she would have invested in conducting the ML operations on their grounds.
Insights for you
After exploring the myths and truths about machine learning, it is time to incorporate it into your business. The experts at DataToBiz are well-versed with the recent trends in data science and excel in machine learning techniques. Let them identify whether it is actually smart insights that your business needs or how can they work upon your data so as to give you what your business needs or you need to design a data strategy for your business. They can help you devise a smooth and comprehensive data strategy to boost your business. To know more contact