What Is Machine Learning, And How Can It Help Your Business?.

From IBM Deep Blue beating Gary Kasparov to Google’s Alpha Go winning the GO games, machine learning has evolved with tremendous speed and proven its potential to uplift the business scenario. If we look at the timeline of Machine Learning and the promises it keeps for the future we can interpret that there will be no option for organizations but to get involved in this technology in order to stay on top of things. If you want to invest in a tech that is so dynamic in nature, it’s integral, dive deep to understand everything it can do for your organization.

What is Machine Learning?

Machine learning stands at the crux of Artificial Intelligence and enables a machine to function like the human brain which can self-learn from experiences and enrich its analyzing capacity with every new experience. In machine learning mechanism, the machine when exposed to various data sets learns from it and with every iteration can give accurate answers to a specific problem. To put in layman terms, machine learning is an algorithm mechanism which functions to solve specific queries without programming by any human and works with higher efficiency than the previous computation.

Machine learning primarily is of 3 types:

  1. Supervised Learning: Wherein the machine is fed with historic labeled data and thus can find patterns faster, implementing them when new data is added to the system.
  2. Unsupervised Learning: In unsupervised learning, the data given to the machine is not labelled and thus the machine itself has to find out the trends and patterns and use the logic for the data sets which follow.
  3. Reinforcement Learning: This is different from the two above, herein the machine is told with which actions are good or bad, like in a standard game of chess you play on your laptop, all the good moves are reinforced in the mind of the machine and thus it follows that route when a similar scenario arises the next time. This approach is independent of structured directions and is said to hold the future of AI.

Why machine learning?

The advent of artificial intelligence and the contribution of machine learning to its success is sufficient enough to say that this is one trend, which is here to stay. In this circumstances should you incorporate it in your business processes?

Machine Learning has the ability to automate human mundane work with high levels of accuracy for any type of data. It can not only classify and cluster data but bring about creative business insights to help in your business decisions. Having productive machine learning resources at your disposal increases speed of analyzing information and saves on costs in long run. Not only as a process but machine learning as a service is gaining momentum and can open brand new opportunities for any enterprise.

 Deep learning and Neural Networks

 Deep Learning and Neural Networks are the two jargons continuously mentioned with machine learning so let us understand what do these two entail when it comes to providing intense machines learning models.

Basically, deep learning is a mechanism or technique for analyzing neural networks. Now, what are these neural networks and what do they do? We all know that human brain is made around the framework of billions of neurons which are connected to each other by pathways, which forms a network. Neurons communicate information to one another and transmit information. When the weighted input signals cross a certain threshold it is referred to as activation. This activation leads to the thinking process prompting various muscles and organs to function in a certain way. These neural networks possess the ability to change and modify themselves with the changing weights of the signals. All of the above tasks are a result of learning and varied experiences a human being goes through. For a computer or any machine to replicate human capabilities to think and function are resultant of the way these neuron networks are replicated, this is where artificial neuron networks come into the picture.

Artificial neuron networks are used in machine learning to find the most optimum solution for any specified problem. The neurons in this network are trained by various learning algorithms which improve the efficiency of the network to predict accurate outcomes. Deep learning is just a fancy word to describe the algorithms put in place to chew raw and unstructured data for feature extractions. Feature extraction thus helps a machine to automatically derive relationships in a data and make meaning of it.

So deep learning and advanced neural networks can process large amount of complex data as it grows by creating more neuron terminals and transformation layers while not compromising on the accuracy of the results obtained.

What can Machine Learning do for you and your brand?

 It is safe to say that marketers have definitely recognized the potential Artificial intelligence for marketing. With the availability of more human like interactive models to keep in touch with customers and provide each with high level of personalization is just what is needed in today’s business hour.

As chatbots and assistant softwares like Alexa, Siri, Cortana etc. become an integral part of the way humans converse or demand, organizations are reaching one step closer to tap into those hidden and latent consumer needs. Not only does this help you understand your consumer better but opens up new avenues to serve your customer better, give him what he needs before even telling it to anyone.

Now you can only imagine what this can do for your brand!

Team your machine learning models with high quality NLP and get the competitive edge, work out business strategies which have higher success rates and create value for your customer by satisfying them. Look beyond the struggle to retain your consumers and find new list of users you never thought you could tap into. With Machine Learning, the possibilities are endless! Get in touch with us to understand how we could help you!

Leave a comment

Your email address will not be published. Required fields are marked *