It should be a rather easy question if we are aware of the advancements taking place in the field of artificial intelligence. Yes, machine learning has everything to do with AI; it helps a computer learn by itself so that it can adapt to new found information and make necessary changes to the program without human involvement. So, it is understandable that machine learning is essential for the functionality of an AI, though it does not explain why we suddenly need people learned in this field so badly. Let us find out.
Machine learning and Big data
Recent developments have enabled machine leaning algorithms to apply complex mathematical calculations to ‘big data’. The association to this pair of words should somewhat explain the sudden rise of importance of machine learning, at least in the main stream industry. Machine learning had always interested researchers more than industrialists; its involvement with big data surely changes that.
We live in a data centric world. From manufacturing to healthcare, all the industries plan every move on the basis of collected and analyzed data. The idea is to look at the history and react to the present and to try and predict the future. The whole concept of drawing insights from heaps of apparently meaningless data is frightening, given the amount of data the world is filled with on a daily basis. The IoT connects everything and everyone in a network that, coupled with social media makes it terribly easy to get lost in irrelevant data. It is quite difficult to deal with that much data and put it into patterns to objectify it. So the problem turns from analyzing data to finding relevant data to analyze. This is where machine learning comes into play and changes the game altogether.
Machine learning as a breakthrough
The early, popular examples of machine learning can be found in Netflix’s movie recommendations or Facebook’s identifying your friend’s face. Google’s self driving car is probably the most intriguing case in machine learning so far. Domingos says. “One stage is where we had to program computers, and the second stage, which is now beginning, is where computers can program themselves by looking at data.” Machine learning automates analytical model building. Now, this small statement has a huge range of implications. A recent report by Mckinsey claims that machine learning is going to be the key factor behind the technological and industrial advancements of the coming times. It does not require a great vision to imagine how big the social and commercial side of this can be.
Big data analytics helps enterprises in making reliable decisions and machine learning helps in analyzing those huge chunks of structured and unstructured data. The fact that makes it possible is that machine learning lives on growing amount of data. The amount and variety of data, that troubles the traditional big data analytics tools, feed machine learning algorithms. More the amount of data you expose it to, more reliable the results.
The Industrial side of things
Businesses are increasingly inclined toward acquiring specific details about individuals in order to find out the most potent consumer base and to place the best offer in front of them at the best time. The trial-n-error method of data analysis hardly works when it comes to large chunks of data. While the revolutionary developments in the field of machine learning are constantly changing the way we look at computing, its applications to fill the gaps in data analytics can be decisive.
Some common instances of applied machine learning are image recognition; fraud detection; network intrusion detection; web search results. It brings on the plate a whole new dimension of possibilities for industries across the world. It has the potential of predicting behavioural patterns of individual human beings; it is like reading the mind of a person to detect her next move. This can revolutionize B2C marketing.
Pharmaceutical and healthcare industries are already making great use of big data analytics. Machine learning renders these industries way more powerful. With algorithms that can study symptoms of various diseases and determine the requisite medication, the worldwide healthcare industry will find many solutions. In the case of retail industries the production will be better targeted for the potent set of consumers. Security facilities and military operations may find great use of machine learning, advancements of bio metric security being one small example.
It is THE skill to acquire
Just as it appears, the exciting and revolutionary field of machine learning is filled with endless possibilities. This explains why this skill is so much sought after. Machine learning is a part of most IT and computer science related degree courses. There are a lot of facilities too that provide industry specific training. This holds an opportunity for the professionals to upgrade their repertoire with the skill that is constantly rising in importance.