The Importance Of Machine Learning In Various Industries

Introduction to Machine Learning

Machine learning is considered to be one of the most evolving technologies that have been evolving in a very fast rate. The acceptance of the technology has been ever increasing, the major reason behind the increase in the acceptance of the technology as that the usage of the technology of machine learning has been increasing the efficiency of the tasks that are being performed. The project that use the technology of machine learning gets the benefit of completing the entire project in a better manner. In case the terminology of machine learning is used in the completion of the project the time that is required in the completion of the project decreases. This also acts as the main reason that the implementation of the entire technology has been increasing.

This report will provide a literature review that will provide a brief ideology regarding the implementation of the project. Literature review is a medium that takes into consideration the prosecution methodology that helps in gaining the data regarding the topic that is being discussed about. This is the reason that the completion of the project requires attaining of the completion of the project. In order to complete the projection of the data management quantitative research is performed that helps in providing the literature review in a much more authenticated manner. The performance of the entire system that indicates the functioning of the system includes the fact that the data that are written in the literature review are gathered from the literature analysis of journals that are authenticated in nature. In order to commence the project with highest efficiency of the project. This is due to the fact that the data that are generated in the project management regarding the commencing of the security issues can be well accomplished with the help of the machine learning.

This report will include rigorous and extensive research n authenticated articles in order to maintain the projection of the data that are useful in the prosecution of the security issues that are present in the course of this project. In order to complete the project management another most important thing that is performed includes the projection of management of technology and use the same in a better proposed manner. In case to gain a better understanding of the technology completion of the literature review plays an important part. This report will state a brief overview of the methodologies that is used by the experts in order to better complete the projection of the task. The security techniques that are imbibed with the help of the machine learning are stated in this report in the section of the literature review.

Importance of ML in Automotive Industry

This report also provides a better convection of the study that is being performed with the help of the data management and a reflection is provided. This reflection help in understanding the problems that were faced during completion of this project this reflection will also state the advantages that were enjoyed during the completion of the project.

The automobile industry is changing rapidly in the recent 5 to 10 years. The market condition is shifting and that is associated with the increased competition. In addition to that globalization, cost pressure and volatility has increased the demand for the innovation. The innovation is required to meet the demand of the consumer for driverless car which is setting the trend in the automobile industry. According to Reijonen et al. (2015) automobile industry need to adopt technology. The reason that machine learning has got so much attention is the potential of the technology in the innovation of driver less car. Driver less car is trained with machine learning with real time traffic simulation. As the car is trained with the traffic simulation it becomes capable to recognize the status of the traffic and it drives the car in the road in real traffic condition without help from actual driver

Machine learning according to is an excellent choice to bring innovation and efficiency in the financial sector. Machine learning in financial sector can be used for offering personalised banking service to the consumer at affordable cost. According to Bocken and Short (2016) machine learning has the potential to analyse huge amount of data in real time. Hence it can be used to identify the nature and authenticity of any transaction by analysing the history of all the transaction that has made by the consumer of that particular account. It will help to identify if the transaction is made by the authentic user or someone else which will make the financial transaction more secure and efficient. Some leading banks around the world have already invested in this kind of project. Although the projects are not fully commercialised, but the technology once implemented successfully with the traditional banking service will revolutionize the financial sector, specially the banking sector as specified by the author

Laukkanen (2015) describes machine learning as the most significant application of artificial intelligence and it has a huge potential in the retail sector. According to the authors as the retail and ecommerce sector is becoming more and more popular, integration of technology is not an option anymore, and it has become a necessity for the business. One of the latest technology which is becoming popular in this sector is the machine learning. As the machine learning has the ability to analyse a lot of data in real time, both in structured and non-structured data, it is being employed for analysing data reacted to the customer service. Ecommerce sites collects data including history of purchase, type of purchase and recommends item to the consumer in real time. As the recommendation is based on consumer preference, it is very likely that the consumer will be interested in that and hence it will helpful for better consumer service and consumer retention through personalised marketing.

ML in Financial Services

Another significant contribution machine learning has to make is in the field of personal healthcare. According to Porterfield (2015) machine learning has to the potential to offer healthcare to each and every patient as per the requirement. When patient are treated according to medical history the treatment becomes more effective and efficient. Machine learning will help doctors to analyse medication data like how well the patient responds to certain medication, what are the medication the patient is prescribed. These kind of information will not only help to diagnose the patient better butter will help the doctor to provide personalise treatment to the patient.

Machine learning is being adopted by technology giants like apple, google, amazon, Samsung for designing virtual assistance. The virtual assistance according to Raisch (2016) is one of the successful application of machine learning. The virtual assistance when asked about certain information scans the relevant information from the vast database and where to search for which information is easily recognised by the virtual assistance. It is possible because the virtual assistance is trained extensively with the machine learning with millions of data so that it can recognise the voice command and interpret information from it.

Warren (2017) has explored the application of machine learning in the field of industrial production. According to the authors if the intelligent robot trained with machine learning are employed in the industry for production it will help to minimize the production cost, reduce production errors and improve efficiency.

  Machine learning according to Dan (2015) is an excellent application in the industrial production as well for designing smart robot for industrial production.

This report has provided me the opportunity to learn the machine learning concept in details. I already heard about the technology but I did not have very broad knowledge about it. So I was very excited to learn a new concept in details.

While I was preparing the report I recognized that I did have very little knowledge about the topic. I thought that machine learning is just what the name signifies. We just need to train the machine. But the actual scenario is not that simple as it involved a lot of complicated process and all if these process have to be clearly integrated for successful application. It involves proper design of software, integration of machine learning code, design of prototype and testing of the prototype. Now in order to recognise successful implementation of the technology for designing a particular prototype all of these process has to be perfectly executed. Honestly I really have not that much idea as I never explored the application of the machine learning in industrial application. I had only idea about the products where machine learning is being implemented, not how it is being implemented. With these report I have gained some knowledge in this aspect also. Though the knowledge is not very detailed, still it has improved my viewpoint about the technology.

Another important thing I learned while I was doing the literature review is that machine learning is an application of artificial intelligence. Before doing the literature review for preparing the report i did not have the idea that machine learning is related to artificial intelligence. In fact I considered both to be different branch of modern technology. Hence with this literature review I became familiar with the technology.

Hence with this report I have enhanced my theoretical as well as practical knowledge about machine learning and its application in details.

References:

Bocken, N.M.P. and Short, S.W., 2016. The theory of machine learning in industrial application: a comprehensive discussion. McGraw-Hill, Inc.

Dan, A., the scope and status of machine learning in industrial application, 2015. Method and apparatus for leading effective project execution.

Laukkanen, T., 2015. The definition and scope of machine learning in object recognition. A modern theory of image processing, 42, pp.35-46.

Porterfield, T.E., 2015. Evaluation of image segmentation: an empirical investigation of scope and success. International Journal of information and technology, 40(6), pp.435-455.

Raisch, W., 2016. Towards a sufficiency-driven image recognition: evaluation of as-Is Workflow Modelling, 18, pp.41-61.

Reijonen, H., Hirvonen, S., Nagy, G., Laukkanen, T. and Gabrielsson, M., 2015. The bias of research method in research. A modern approach, 51, pp.35-46.

Warren. N, 2017, January. The importance of machine learning for successful research implementation: an intuitive guide.