Future job prediction in Trivandrum using machine learning techniques
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Saju, Akku George
MSc in Information Systems with Computing
Dublin Business School
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This dissertation explores the impact of machine learning on job aspirants through an interactive web application. Job seeking is a very difficult task in India and determining a career path is a much more difficult challenge. There is a lack of planning in the life of job aspirants. Job aspirants don’t get enough updated information regarding the job opportunities in different sectors. There is a need of a proper medium through which job aspirants could get information on the number of job vacancies, number of intakes, salary etc. in each job industry for the future years. Using such predictions, job aspirants can plan on a specific career path and the specific qualification required for the job can be attained in the following years. Nowadays, websites act as a powerful medium to reach to the job aspirants. The major contribution of this dissertation will be a web application using angular platform, through which job aspirants get updated knowledge regarding future job opportunities in the form of statistics, charts and graphs. Therefore, this dissertation endeavours to minimize the challenges faced by job aspirants through machine learning techniques. The study was conducted by adopting a mixed method approach: both statistical and predictive in nature. Decision tree, linear regression, decision forest and neural network regression are some of the machine learning algorithms considered in this study. The key findings using these algorithms are also displayed in this study.