— Jitendra Kumar Mishra
Machine learning is a method of analysing data that automates analytical model building. It is a part of Artificial Intelligence (AI) that uses the idea that systems are able to identify patterns from data and can make decisions with minimum human intervention.
This iterative aspect of pattern recognition and computers learning from data without being programmed for specific tasks finds application in self-driving Google cars, practical speech recognition, effective web search, online recommendations from Amazon and Netflix, knowing what people are saying about you on Twitter, and fraud detection. ML is increasingly becoming all-pervasive and we may often be using it without even knowing it.
Currently, there exists a thriving magnitude and variety of data, cheaper and more effective computational processing, and inexpensive data, all of which have reignited interest in this concept. It is now quite possible to create models that can analyse larger and more intricate data and arrive at authentic results within a smaller period. Organisations today are using the concept of machine learning to identify money-making opportunities and avoid unknown risks.
Career in ML
Machine learning is fast becoming one of the most sought-after career choices available. According to Gartner Inc., leading global research and advisory firm, AI-related job creation will reach two million net-new jobs in 2025. It says that AI and machine learning will become a positive job motivator in the foreseeable future. We would need to rethink our mindsets and be open to be rapidly adaptable to AI- related opportunities and threats to make the most of the opportunities though.
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Data Science and Machine Learning are two of the fastest-growing tech employment areas today. Employers are looking out for technologists who can carry out a variety of tasks from analysing data to building applications. The ML scientists would be assets to the companies they are working for, building methods for predicting product suggestions and product demand and exploring data to extract patterns automatically.
Subjects to learn ML
Machine Learning is a popular domain as it brings down a lot of human efforts and enhances machine performance by enabling machines to learn for themselves. Some of the skills sets needed to become a machine learning professional include computer science programming, machine learning algorithms, probability and statistics, and software engineering and system design.
Equipped with these ML skills, a young individual today can get productively employed as machine learning engineers, data scientists, data mining specialists, cloud architects, and cybersecurity analysts in different domains in an age where Artificial Intelligence is predominant.
Machine learning engineers use programming languages such as Python, Java, Scala, and more to run various machine learning experiments, where the behaviour of algorithms on specific problems are learned empirically. The skills needed for this include programming, data modelling, system design, probability and statistics, and machine learning algorithms.
A data scientist collects, analyses and interprets large volumes of data using advanced analytics technologies to arrive at actionable insights which are then used by company executives to make business decisions. In addition to ML, some of the other skills needed for this position include knowledge of statistical research techniques, data mining, and programming languages such as Python and Scala.
An NLP (Natural Language Processing) scientist assists in the creation of machines that are able to learn patterns of speech and also translate the spoken words into other languages. Cybersecurity analysts protect sensitive information and proprietary data of businesses and organisations from cybercriminals.
Students wishing to stay ahead of the technological changes can opt for a postgraduate programme in AI or Machine Learning in general and any of the specific topics in particular from well-known universities including IITs which offer a BTech in Artificial Intelligence. Through these programmes and modules, they can get introduced to machine learning, data mining, and statistical pattern recognition, and also gather the experience and expertise to stay fully prepared for big data and data science.
— The author is director, Jaipuria School of Business, Ghaziabad.