The developing interest of Machine Learning (ML) in pretty much every industry is convincing the representatives over the globe to learn new aptitudes in comparative territories. It is said that ML is relied upon to affect and change our lives in manners past creative minds like the web. Computer-based intelligence/ML will change how we shop, convey, travel, play out our normal undertakings, and do our business.
Machine Learning experts prepared in the field of Machine Learning are sought after. Pretty much every startup (programming based), just as an enormous undertaking, needs to enlist talented Machine Learning experts. In this way, if an individual needs to find a new line of work in the field of Artificial Intelligence, it is the best ideal opportunity to upskill with one of the urgent parts of AI, named Machine Learning.
What is Machine Learning?
Machine Learning is the process through which a machine learns autonomously without being explicitly programmed. ML is a subset of AI that enables a mechanical system to learn automatically and improve from experience by incorporating input and output of the program.
Machine Learning: Future Prospects
A recent report by IT firm Accenture suggests that Machine Learning has the potential to contribute nearly $957 billion to the Indian economy by reshaping work dynamics and fostering better outcomes for businesses. The report, titled 'Revamp for Growth,' predicts that ML intervention could increase India's annual growth rate of gross value added (GVA) by 1.3 percentage points, thereby boosting the country's income by 15% by 2035.
Moreover, the growth isn't confined to Machine Learning alone. Research from Markets and Markets indicates that the Machine Learning market size is projected to reach USD 8.81 billion by 2022.
Given the multitude of opportunities in this field, now is the perfect time to upskill in Machine Learning to pursue any of the following job roles.
Machine Learning: Job Roles
Let's take a sneak peek into some of the in-demand ML job roles. Machine Learning jobs for freshers may encompass positions such as software engineer, data analyst, or data scientist.
- Machine Learning Engineer: Responsible for designing and implementing AI algorithms.
- Data Scientist: Gathers, analyzes, and interprets large volumes of unstructured data using ML and predictive analytics to derive insights and aid in future strategies.
- Data Analyst: Acquires, interprets, and analyzes information about specific subjects, presenting findings as comprehensive reports.
- Data Architect: Develops, tests, and maintains highly scalable data management systems using Machine Learning algorithms.
Machine Learning: Average Salaries
Salary packages for Machine Learning Professionals vary based on qualifications, job roles, profiles, and years of experience. Freshers typically receive annual packages ranging from 6 lakhs to 9 lakhs per annum.
Top Recruiters
The following is the rundown of some eminent organizations that enroll Machine Learning experts
- Amazon
- Apple
- Microsoft
- Bosch Group
- Adobe
- Accenture
- Wipro
- JP Morgan Chase and Co.
- Uber
Machine Learning Engineer
With a median salary surpassing $100,000, Machine Learning engineers are among the most sought-after positions in artificial intelligence. They possess expertise in programming, natural language processing, statistics, applied mathematics, and hands-on knowledge of tools such as IntelliJ, Eclipse, among others. Aspiring Machine Learning candidates should consider delving deeper into becoming Machine Learning engineers.
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Conclusion
To pursue a career in Machine Learning, one must be well-versed in the practical implementation of ML algorithms, which are widely available through libraries/packages/APIs. These algorithms constitute one of the most essential components of Machine Learning.
The world is increasingly turning to Machine Learning, with startups and tech giants offering lucrative salaries for sought-after Machine Learning roles such as ML Engineers, Data Scientists, etc.
Forbes predicts that theoretical research in ML will gradually pave the way for business problem-solving. With Big Data becoming integral to mainstream business activities, smart ML algorithms can utilize vast amounts of both static and dynamic data to continuously learn and enhance performance. In research areas, Machine Learning is moving away from abstractions and engaging more in business problem-solving with the support of AI and Deep Learning. The growing trend of deploying prebuilt ML algorithms to enable Self-Service Business Intelligence and Analytics signifies a positive step towards the democratization of ML.