Why is machine learning an in-demand skill?
https://www.coursera.org/learn/machine-learningThe ever-changing word of technology poses not just an interesting proposition but a challenging one too. The rapid transformation in processes and the way the world is gradually adapting to it makes for noteworthy observation. Activities which used to be a part of our lives till a decade back are now redundant and has been taken over by algorithms which are intuitive enough to understand our needs and demands. In this fast-paced society it is essential that decision making does not pose as a roadblock. In a lot of circumstances, it has been left to the machines to undertake this arduous task of taking decisions. But it is not some random decision-making endeavour but an extremely well thought out one, supported by reams of data and stimulations, predictive analysis and forecasting. Welcome to the world of Machine Learning.
What is Machine Learning?
Machine Learning is a form of Artificial Intelligence (AI) process where the software application becomes independent of human commands and can predict outcomes on its own. One of the manners in which this is achieved is by recording historical actions and then embedding it within the application. Machine Learning has over the years revolutionized a set of industries and helped them improved both their efficiency and productivity. A host of verticals use Machine Learning to fulfil their needs. One of the major users of Machine Learning are the financial institutions. They use it for a variety of reasons but more importantly to weed out unscrupulous transactions and detect frauds. Banks undertake humongous number of transactions each day. And it is not just transactions that take place in any financial institution. There are other activities too. No bank in the word will ever have enough manpower to deal with everything and everybody. This is where predictive technology appears. Machine Learning analyses the patterns and the trends and then investigates transactions to check for any wrongdoing. Even mundane tasks can be achieved through Machine Learning.
One of the biggest beneficiaries of Machine Learning have been ecommerce companies. They are also one of the reasons why these technologies have become so immensely popular. Ecommerce companies like Amazon, Alibaba, Walmart use Artificial Intelligence for myriad jobs. They use it to study consumer behavior, trends and best sellers, regions of high and low growth and so on and so forth. Machine Learning is an integral part of the entire technology structure of most companies nowadays.
Why is Machine Learning Important?
One of the most important reasons why machine learning is being used extensively by organizations globally is because it can augment the effort of many human resources in the shortest span of time. Complex calculations and analysis get completed quickly and at the best possible accuracy percentage. Machine Learning has been able to provide organizations with the competitive edge that is needed in this age of cutthroat competition. Companies must keep in mind the rising cost of resources and marketing campaigns and implementing Machine Learning processes is one of the ways to keep one competitive.
Types of Machine Learning
There are four types of Machine Learning processes:
In this type of Machine Learning, data scientists supply the algorithm with the necessary data and then define the variables. They then ask the application to assess the correlations. In supervised learning both the input and the output are specified.
This type of Machine Learning involves algorithms that train on unlabelled data. The algorithm studies the data and then searches for any relevant correlation. The data will generate an output that it has been trained on. In such a type the output is predetermined.
In this type of Machine Learning, a mix of both Supervised and unsupervised learning is used. Data scientists will feed the algorithm with training data but will allow it to analyse the data in its own manner and develop its own understanding of it.
Data analysts and scientists use reinforced learning to train the algorithm complete a multi-step process using well defined rules. The process is then allowed to be completed with the help of positive and negative cues as provided by the data scientists to the algorithm. However, in this type of Machine Learning, the algorithm completes the task mostly on its own.
Industries and the Usage of Machine Learning
Customer Relationship Management or CRM is a popular tool which most consumer facing organisations use to interact with their consumers. This software is also used to track activities, answer and notify emails, set up inter department meetings et al. CRM is often used by the Sales and Marketing teams to track data and reach. Intelligent CRMs have automated response systems as well predictive capabilities to assist the user in improving productivity and better revenues.
Business Intelligence or BI is the next frontier of technology. A variety of jobs is fulfilled through BI. Organisations invest a lot of money into BI systems to help them gauge consumer trends and sales patterns. Business Intelligence accompanied with Machine Learning can help in identifying myriad data points, anomalies arising out of unstructured data and patterns and correlations getting created amidst the ocean of numbers. Business Intelligence is extensively used to number crunch in organisations who deal with a constant flow of information and figures. Business Intelligence is one of the leading domains where Artificial Intelligence can make a big and effective difference.
Semi-autonomous cars are the future rage and what was deemed to be near impossible, Machine Learning is gradually making it quite possible. Semi-autonomous cars can identify obstacles on the road and is powerful enough to even predict potential hazards. Machine Learning even makes it possible to help the car identify a semi visible roadblock and send alert to the driver. As the technology matures further, the transformation of Semi-autonomous would be even more dramatic and given the way it is growing, cars would become completely autonomous devices and have their own capabilities.
Smart assistants, like semi-autonomous cars were also an unthinkable concept till a few years ago and today it is one of the most sought-after technologies globally. Virtual Assistants or VA use a mix of supervised and unsupervised Machine Learning to fulfil responsibilities. Its powerful algorithms allow it to interpret natural speech, help in translations, compute complex possibilities and supply text.
Machine Learning is an in-demand skill for a variety of reasons and in order to know that let us first investigate the advantages and the disadvantages of it.
It helps the companies to understand their customer base more deeply. The complex patterns and trends and their correlations with external influences can be computed with fair precision and at double quick time. Machine Learning also helps companies to predict and forecast the business environment in relationship to the past historical data and current scenarios. Such predictions and forecasting are necessary for management teams to take informed decisions pertaining to their business models. Ecommerce companies use Machine Learning to analyse consumer spending capabilities and product sales.
Internet advertising companies use Machine Learning to understand the search patterns of users and then help their clients reach the potential customers through predictive analysis. Google uses Machine Learning extensively to help advertisers reach their potential.
First and foremost, Machine Learning is an expensive affair. The technology is not cheap to build or maintain. One of the primary reasons for it is the availability of data scientists and analysts. These individuals are highly experienced and knowledgeable in their field and command a high remuneration. It is therefore pertinent for organisations to do a cost-benefit analysis before plunging into using Machine Learning. The long-term cost of using Machine Learning may end up as a burden for the organisation who would be saddled with high salary bills.
Machine Learning relies on data sets which may end up having errors or certain biasness. A system trained on biasness will generate incorrect reports. This is a common challenge for organisations using Machine Learning. Inaccurate models are a result of such biasness. This biasness may occur due to incomplete research, incorrect data reporting or in the worst case, discrimination. If such a circumstance occurs, then there is a high possibility of regulatory and legal proceeding against the organisation propagating such a data.
Why is Machine Learning an in-demand skill?
Coming to the prime question of this article, the above set of information is ample proof illustrating the role Machine Learning will play in the future. However, if someone, who is yet confused regarding its prospects, let us quickly look at the reasons making Machine Learning a popular job today.
Machine Learning is the future of technology. In fact, Machine Learning is the future. There is a scope of explosive growth, and this skill will never face obsolescence. Currently companies are looking for knowledgeable professionals who will be able to drive growth and Machine Learning is playing an important part in it. Any confusion pertaining to future viability of the technology should be put to rest.
As a Machine Learning specialist, one will be able to work on the real challenges that companies face while trying to expand their reach and network. Organisation would want to understand the bottleneck and roadblocks that may appear during growth. This information is gathered through reams of numbers and statistics and data scientists will have to segregate them based on categories. Machine Learning helps speed up this process and with precision. Machine Learning jobs enable individuals to get experience of challenging real-world scenarios.
Great Learning Opportunity
Machine Learning is a growing and an expanding technology which enables its users to learn and grow along side. With greater experience one will also be able to command a decent salary increment while changing jobs. The other salient opportunity that Machine Learning gives to its users is that it is a new technology and there are still many aspects which are yet to be discovered. Hence, this too is an enabler for growth.
Career graph on a rocket
The growth of a Machine Learning specialist is explosive. Given the rise of the technology and the high demand, data scientists are an absolute necessity. As the technology matures and adoption becomes streamlined, the demand will simply hit the roof. This is the time when data scientists need to buckle up and know heir worth in the market.
All the above points illustrate one truth; the salary that data scientists can command is simply astronomical. Given the paucity of qualified professionals and the high demand, professionals are well placed to negotiate favourably. They can even ask for benefits alongside their annual remuneration as an incentive. The industry is on a roll right now and perfectly ready for the influx for many professionals to take the plunge.
Machine Learning is a skill that can be mastered in a silo. There are many aspects to it, first and foremost being data science. A well-qualified Machine Learning expert will also have to have innate knowledge of data and their characteristics. This is the base for data science. Machine Learning provides ample opportunity to professionals to sidestep into the world of academics in the form data science, artificial intelligence and its many forms et al. The biggest advantage is that both these disciplines are mutually inclusive and work hand in hand. As a matter of fact, professionals can opt for any other numerical discipline while working on Machine Learning since the horizons it opens is vast.
Machine Learning is a vast world and there are numerous scopes waiting to be taken advantage of. The demand is growing by the day though the supply remains low. A prime reason for that being the vastness and the complexities of the subject. One must persevere to master the huge concept even before being able to operate Machine Learning tools. The growth of ecommerce has pushed the need of artificial intelligence in a major way and with each passing day, this demand will rise. Now is the time to take the plunge.
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