The world is full of data – images, documents, music, video content etcetera. And it doesn’t look like as if it’s going to slow down anytime soon. Machine learning helps us acquire meaning from the data. The tools and the algorithms we use to get answers to tricky questions achieved with the help of machine learning. As we all are aware of the fact that humans learn from their past experiences and machines work with the instruction given by humans. Now, what if we can train our computers to consider their experience (previous data) and work accordingly, just like humans. Well, that’s pretty much it, what we call machine le
Let’s try to understand machine learning in a more straightforward manner.
For instance, while preparing for school examinations, you put in all the necessary information into your head, and you try to learn the subject with complete understanding. Each time you evaluate your performance, the results keep on getting better, and your confidence continues shifting to a higher level. That’s how we can build models to train the machine to use their previous experience and perform a specific task.
The first step of the process is to develop tools and models for machine learning with the use of data structures and different algorithms. Then feed the machine with good quality data.
How Machine learning works in reality?
Since 2005, Youtube has been trending more than any other application we use within our daily lives. This might set the perfect example of how machine learning works in reality. If you frequently watch videos of a particular genre, the more your feed will fill with the same type of videos. Through ML the software is trying to predict the preferences of the user, and with the help of statistical analysis, it manages to fill your feed with the same.
While we spin the factor about people juggling with different choices online as there are a million of them who regularly have a lot in their search option, searching a product frequently can make the buyer’s web pages, Facebook, Instagram, all advertising for the same product. There is no one sitting behind and performing this task. ML here is performing its job with the previous data recorded and is also improving with time and experience. Data scientists and researchers build models for machines and put an enormous amount and good quality data into them.
Earlier, the advertisement was only dependent on magazines and newspapers, but as time has evolved, technology has become more efficient in reaching its targeted customers.
Healthcare has improved as well due to improved technology. A machine can even detect cancer at a very early stage by just looking at the cell. Performing a similar task physically would take a lot of time. Thanks to machine learning, scientists have been building models with the help of high-quality image data and proper computation to detect if someone has a tumor or not. ML developed with functional data structures, and accurate algorithms can even diagnose patients based on different parameters under consideration.
Evolution of ML
Machine learning has been in existence or a considerable period.
But the growth has been radical in the past few years. Earlier the tools used for machine learning were very pretty much straight forward than the current ones. There was a set of machine learning tools for the computer system built on the base of the human brain and nervous system which is becoming popular now. Machine learning is one of those few technologies which will become one of the most trending technologies in the coming 3-5 years, and a significant amount of crowd will lean towards it. Capabilities like the infrastructure and technical improvements might also help machine learning to become one of the mainstream fields shortly.
Future of ML
The reason why we think that machine learning will take over almost all the jobs in the near future is because of the advancements in technologies.
We have indulged into deep learning for quite a long time now, but what we were missing out on was the power to run algorithms. In the past few years, power has dramatically evolved. For example, if now we run our algorithms with the advancement in infrastructure and with the access to better and developed data, we get tremendous results. All we can say is from here it’ll only get better. In the foreseeable future, we are expecting our machine to recognize emotions as well which will be a massive shift from what it is right now. Machine learning is supposed to be solving problems in lots of areas single-handedly in the foreseeable future.
Now that you are aware of how machine learning works, you should also be conscious of the fact that it is one of the fastest-growing jobs right now. Visit Coding Ninjas to ensure you are well prepared to make a solid career in machine learning.
Read more about Machine Learning and which projects that you can make in Github, here.
