What is machine learning an introduction?

In simple terms, what is machine learning is a concept that computers can study without being planned to do a precise task. In technical terms, machine learning is an iterative aspect of a computer to perform a task independently using the data – it means they can independently adapt. They learn from preceding computations to produce dependable, repeatable judgments and outcomes. Here is a classic picture to explain the use cases of what is machine learning? 

In today’s world, machine learning is just not a discipline that is new – but one that has gained larger importance in the business world and momentum for job seekers. A recent publication named,   “Predictions 2020: Automation” quotes that around 1 million work jobs will be completely replaced in 2020 by machine learning-based decision management or virtual agents or by software robotics which upsurges the opportunity for machine learning experts. 

Importance of machine learning in today’s business world

With the availability of a huge amount of data and affordable computational processing, today’s business can identify potentially profitable opportunities or identify potential risks through machine learning. By utilizing the expertise of machine learning engineers, a business can build models that can open up various decisions without a large amount of human intervention. Businesses covering retail, financial, government, health care, transportation and oil, and gas are the major benefiters of machine learning. Using machine learning technology most of the companies are able to gain a larger advantage in comparison with their competitors. Here are a few industry examples who feel the importance of machine learning – 

  • Retail: Machine learning technology in retail business helps websites in giving a recommendation to consumers on previous purchases and search history. Personalization, price optimization, review of customer insights and supply planning are the outcome of machine learning in most retail businesses today. 
  • Financial services: The banking sector uses machine learning in the most important aspect of fraud identification and prevention. Further, the larger advantage of machine learning in banks is the use of data to draw insightful information to help investors in investment planning and trading. 
  • Government: In the case of Governments, in many use cases, various departments use machine learning technology in the distribution of funds to appropriate category people and public data are mined for useful insights. 
  • Health Care: Machine learning technology and requirement in machine learning jobs are fast-growing in the health industry today. With the advent of low-cost sensors, the health industry is getting huge data, which are later used for offering insightful real-time information to patients making this sector attractive for jobs and investment. The interesting part is that machine learning technology today can also diagnose skin cancer by reducing human errors, Springboard’s article on Machine Learning Applications for Skin Cancer Detection can help you know more about the developments in health care industry of machine learning. 
  • Oil and Gas: This industry uses machine learning and artificial intelligence to the core. The MI/AL technology helps the oil and gas industry in improving efficiency and making process cost-efficient. 

Businesses today consider the machine learning engineer role a key aspect in their decision-making process and strategy building for the future. This is making the career prospects for machine learning engineers attractive. According to the research report published by the insight partners, the global machine learning market is expected to grow at a CAGR of 49.7% between 2017 and 2025 (2017: US$ 1582.9 Mn in and 2025: US$ 39986.7 Mn). Large multi-corporations, start-ups and public-sector companies are looking for machine learning experts to fill their digital transformation team. If you want to know what are the prerequisites being looked for in a machine learning expert you can refer to springboard’s article on Machine Learning Prerequisites for Beginners to know more. 

Machine learning jobs are attractive today!

The best part in the recent development of machine learning jobs is that, unlike the past where engineers were asked to work on machine learning algorithms, today the things have changed faster where engineers focus on automatically solving complex tasks with big data. Here are a few attractive cases, which are the output of machine learning engineers – 

  • Recommendation to consumers on a day to day basis online by Amazon or Alibaba or Netflix is a result of machine learning data analytics.
  • Self-driving car by Google or Tesla is the essence of hard work developed by machine learning engineer. 
  • Machine learning combined with linguistic rule creation for analyzing and directing consumer behavior on social media platform is a result of machine learning. 
  • Improved content discovery in Pinterest is the outcome of machine learning. 

Kinds of jobs offered in Machine Learning Domain

Keeping the pace with technological innovation and business requirements, jobs in machine learning covers the following core areas – 

  • Software Engineer
  • Software Developer
  • Designer in Human-Centered Machine Learning
  • Data Scientist
  • Computational Linguist
  • Machine Learning Engineer
  • Data Engineer/Data Architect and 
  • Data Analyst

If you are interested in taking an opportunity in Machine Learning Jobs, then take the next footstep, join the Springboard’s attractive machine learning program which will help you in developing the required business skillset.