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Machine Learning Assignment On Implementation Of Artificial Intelligence In JD


Task: Students are required to write an academic report as per the format outlined in chapter 5 of the textbook. The report must follow the CQU APA referencing style. See the American Psychological Association (APA) abridged guide updated Term 1 2019 available from: CQU APA referencing style. Please note that the prescribed textbook uses APA referencing guidelines. See also the Referencing Style subsection below.

The report is to be based on the following case study.

Background context: Without referring to a rigorous definition of intelligence, which one of the following is more intuitively intelligent? An iPhone or a 5-year-old child? One would reasonably think that a 5-year-old is more intelligent not because they can perform complicated calculations at their age but because they have the potential to learn to perform well in a variety of settings.

The ability to learn is an integral part of intelligence. Thanks to the ever-increasing computational power, much advancement has been possible in the field of machine learning, which is fundamentally concerned about how we can build computer systems and algorithms that can automatically improve with experience.

Some machine learning algorithms mimic the way humans learn. Whenever they make a mistake, they receive a punishment; whenever they perform well, they receive a reward. Assuming machines are programmed to maximise the total reward, over time they will learn to choose actions that lead to reward rather than punishment. This particular type of machine learning is called reinforcement learning.

Machine learning has been adopted in an increasing number of applications – it is the backbone of many well-known applications that we use every day, for example, face recognition, natural language processing, fraud detection and personalised recommendations on Netflix, Amazon and Youtube

Case study situation: You are an IT consultant of a consulting company. Your company has an excellent track record for applying innovation to unlock trapped value within their clients’ organisation and helping them to embrace IT innovation. One of your clients, JD has recently contacted you to prepare a document on the use of machine learning in their company.

Here are the details of your client company: JD is an Australian online retailer that sells a large range of merchandise, including consumer electronics, apparel/accessories and books to customers worldwide. With the mass adoption of e-commerce, JD saw a robust increase in sales over the past decade. However, as the big players in this industry continued their quest to capture market share, shoppers around the world only spent A$200 million on retail goods purchased on JD’s online store over the past 2018/19 fiscal year. This is 20% down from the A$250 million of the previous year.

The Chief Technology Officer (CTO) of JD believes the application of machine learning in their company equates with future business success and is keen to increase the role that machine learning plays in their customer’s experience. “Consumers expected personalised recommendations tailored to their individual tastes and preferences. Many online retailer platforms have embedded machine learning algorithms to entice customers and to make sure they keep coming back to their online retail stores”, said the CTO of JD, “machine learning can also be applied in other business functional areas, for example, automated resume screening in HR, to increase the overall business efficiency to gain a competitive edge in this industry”.

Before JD shifts their IT strategy to embrace the power of machine learning, they want your organisation to prepare a document addressing the following tasks:

(1) Explain the definition of machine learning, and the difference and relationship between artificial intelligence and machine learning;
(2) Survey the application of machine learning in three different industries other than online retailer industry/ecommerce;
(3) Investigate how machine learning can be adopted in JD. Discuss its application to at least two different business functional areas of JD; and the advantages and disadvantages of its application.
(4) Discuss the ethical, legal and social issues about the application of machine learning on online retailer platforms;
(5) Make three recommendations as to how JD can adopt machine learning in their business.

You have to complete this investigation and write a report for your team leader in the next three weeks. Since this is an initial investigation the report should not contain in-depth technical details.


The present study of Machine learning assignment explores the concept of Machine learning as a part of technological advancement which uses artificial intelligence and enables the system to update and improve automatically without the intervention of human beings. Through using artificial intelligence, machine learning assesses existing data and the system gets updated or improved automatically. Machine learning- the term actually means the learning of the system automatically without any help, from outside. Among the machine learning methods, some methods are categorized as supervised, and some are not. For a better understanding of machine learning, it is needed to focus on the machine learning methods. The procedure of machine learning of method by supervisation is seen to the new data after assessing past or the existing data to forecast about the future. The machine learning algorithm which is not supervised can be used to the data which is still not segregated or classified. There is an existence of semi-supervised machine learning which can be applied to the data, supervised or unsupervised. It can be generally applied to the lesser amount of classified data and higher amount of non-classified data. With the help of reinforcement algorithm of machine learning, the associated systems get enabled to run trial and error method and delay reward. Having the support of this machine learning, proper information assessment takes place through trial and error method. Machine learning assesses a huge amount of data in the system. Based on the assessment of data in this Machine learning assignment, it brings out the accurate result about the threats and risk factors. The mingling of machine learning with artificial intelligence and cognitive skill has made it more efficient and prompt in assessing the massive amount of data of any organization.

Defining the machine learning
In general terms, machine learning refers to a kind of implementation of artificial intelligence that gives the computer systems the capability to automatically gain knowledge of the application and develop from experience without being transparently programmed. Machine learning gives focus on the improvement of the computer programs that have the ability to utilize data after accessing it themselves. The procedure starts with the monitoring data in the form of examples or instructions to look for the various patterns in data and take conclusive inferences in the upcoming years. The basic aim of machine learning is to make allowance for the computer systems to gather the required knowledge automatically and more importantly, that too without the intervention of people and thereafter adjust the working procedures accordingly. Machine learning algorithms are often classified into the below categories such as:

Supervised machine learning algorithms: Such type of machine learning algorithms can be applied that had been gained in the previous years through new data by utilizing labelled examples in order to guess events of the upcoming years. The supervised machine learning algorithms begin with the investigation of an acquainted training dataset, and it tends to generate a certain function to make guesses about the output values. After the completion of efficient training, the computer system can give targets related to new input. This learning algorithm does have the ability to make a comparison of its output with the proper intended production and look for errors for the sake of modifying the model accordingly.

Unsupervised machine learning algorithms: Non-supervised machine learning algorithms mentioned in the Machine learning assignment are utilized when the data used to give training is not divided and labelled. This type of learning makes a study on how the computer systems can deduce a function to narrate a hidden structure from unlabelled information. The systems do not have the ability to decide the correct output that is needed. However, it has the ability to make an exploration of data and can extract conclusions from the dataset in order to make a description of those hidden structures from unlabelled information.

Semi-supervised machine learning algorithms:  Such type of machine learning algorithms fall in between supervised and not supervised machine learning algorithms because these algorithms both utilize labelled and unlabelled information for the purpose of training. The computer systems that utilize this process are able to make an improvement in learning accuracy. This type of learning algorithms is generally chosen when those gained labelled information needs skilled and useful resources for the purpose of either training it or take learning from it.

Artificial intelligence and machine learning relations
In general terms, artificial intelligence is associated with the theory and improvement of computer machines that can carry out tasks automatically without human intervention. The tasks performed by artificial intelligence are identification of speech,.Visual perception, making important decisions and making translations in various languages. Om another way, it can be said that it is a part of computer science that looks to make effective intelligent systems in the form of machines. In fact, with the rapid advancement of technology, it indeed has become an essential rather integral part of the technology industry nowadays. In this context of Machine learning assignment, it needs to be stated that the systems of artificial intelligence possess the capability to carry out various tasks that are closely linked with human intelligence. Due to this reason there has been seen a growing upsurge in adopting this technology more and more in performing the digital activities nowadays. Artificial intelligence has been there for a long period of time. Since the technology and the thinking capacity of humans have changed therefore, there has been a change in the components of AI.

On the other hand, Machine learning is considered to be one of the most extensively used algorithms of artificial intelligence. Machine learning is considered to be the subset of artificial intelligence that different machine learning can be counted as artificial intelligence but the reverse is not possible. For example rules engines, knowledge graphs can be counted as artificial intelligence, but both of them does not fall under the category of machine learning. One perspective that makes the separation between machine learning and knowledge graphs is that its very capability to change itself when revealed to more data. Machine learning is dynamic in its nature, and it does not need the intervention of humans in order to make any changes in it, which makes it less breakable and least dependant on humans.

Survey of the machine learning in three industries
The application of machine learning is gaining overtime in many industries of Australia, and the result of applying machine learning is stated in this Machine learning assignment in detail:

The application of machine learning is increasing in the teaching & learning industry of Australia. Machine learning is highly used in various educational institutes for assessing the student's data. The number of students in govt. And private educational institutes are too high and to keep the account of the student record, the application of machine learning is effective. If the students are attending classes every day or they are not coming to visit the maximum classes days of the week -all these can be counted by assessing student's data through machine learning. The annual attendance report of the students gets published quickly by assessing the previous student's data. This helps the faculty members to understand and bring modification to the teaching procedures to keep the students motivated. However, the application of machine learning in the teaching and learning process is really effective for both students and teachers.

The application of machine learning has become obvious in the mechanical industries. In the various supermarkets of Australia, few staff and employees can be found as the maximum job is done by machines. In the various mines of Australia, it is seen that the trucks and other vehicles that carry raw materials can be controlled by remotes from a particular distance. However, the labour of human workers is decreasing by the use of systems which are equipped with artificial intelligence. On the other hand, it is also mentioned in this Machine learning assignment that the performance of the workers in the industry can be assessed easily by the collected annual job reports of the employees (Bishop, 2006).

Machine learning with the help of artificial intelligence is on the way to bring miracle in the transport industry. Machine learning targets to bring self-control transport in Australia. It is almost calculated that the ships and the railways will be self-controlled in the next decades. Australia is going to launch the fast driving ships which will be fully self-controlled almost in or by the end of 2020. The new addition to the transport system of Australia is the bus which will be driven autonomously and not by the help of the drivers. Still, there are some limitations of machine learning like the acute and the minute task will not be performed by machines. Therefore, it is evident that many employees are going to lose a job for the increasing popularity of machine learning in the Australian business market (Kotsiantis, Zaharakis&Pintelas, 2007).

Adaption of machine learning in JD
JD is one of the famous online retailers in Australia, which generally sell electronics, books and other necessary products to customers worldwide. This organization not only sells products to the customers of Australia but to customers worldwide. E-commerce has given a great platform to the organization so that the customers worldwide can place orders online. The installation of machine learning in JD can be based on some steps. At first, it is needed to frame the problems of the organization. The data of the organization will be modified on the basis of the problems, identified and then the data of the organization can be processed for ML Application. A model of machine learning should be developed with the assistance of the technically sound persons. The model is needed to be improvised and developed from time to time for the proper application of machine learning (Mahdavinejadet al.2018).

The application of Machine Learning in functional areas of JD
On the basis of the business structure and policy of JD, machine learning can be implemented to the performance assessment of the employees in the organization and daily transaction. JD accumulates monthly performance report of the employees in order to understand the level of performance of the employees and staff. Assessing the existing data of the performance of the employees, this new technical application can help the authority of the organization to understand the drawbacks of the organization. Artificial intelligence, rather, machine learning can be applied to the systems that deal with the daily economic transaction in the organization. Assessing the existing data and the new data, a complete error-free financial report can be published.

The advantages and disadvantages of the implementation of machine learning discussed in Machine learning assignment:
Though the machine learning has brought a miracle in the field of technology, the result which is displayed by assessing the data is not error-free always. Sometimes, the wrong result is published by the system which is using artificial intelligence and that affect the overall policy and calculation of the organization. Not only that, the installation of machine learning consumes a huge amount of money which cannot be afforded by all organization. However, the lack of fund is another obstacle in the way of installing machine learning in systems by small organizations (Wuest, Weimer, Irgens&Thoben, 2016).

The social, legal and ethical issues associated with implementation of machine learning for online retailers
Ethical issues of machine learning: There tend to be some ethical issues off machine learning, like, machine learning algorithms can be at times black boxes in nature where it is not possible to observe in which ways they really perform the tasks. It, at times becomes very much difficult to understand the reason for which machine learning algorithms make a decision. In this context, it needs to be mentioned one that there tends to be one specific area of machine learning that is known as making medical diagnoses. An algorithm has the ability to look out cancer through conducting XRay. Though the doctor can give sufficient reason for making the diagnosis it is impossible to know how a machine learning algorithm can determine whether a patient has cancer or not.

Development of training data for machine learning is associated with certain ethical issues. The programmers of machine learning who built these algorithms generally compare black people with the gorilla and the white people are treated as beautiful, which is wrong. Therefore it can be an ethical issue of machine learning. Another ethical issue of machine learning is the safe utilization of machine learning and artificial intelligence. It could give birth to such behaviour that human would not want them to develop.

Legal issues of machine learning: There tend to be some legal issues of machine learning. Since the time of Industrial Revolution technology has been developing very thick and fast, much quicker than the law can cope up with. Therefore when legal issues come to the forefront, they are considered to be the case of the first impression.

Recommendations for JD to adopt machine learning for its business
The three recommendations provided in the study of Machine learning assignment are mentioned below:

i) The Australian JD company can implement the machine learning in their business ni order to sell products to its customers. The machine learning assists in making intelligent recommendation engines that will be able to propose the correct products at the right time to its customers.

ii) The JD can look for those experts that have the experience of building artificial intelligence and can suggest the procedures of machine learning through which their business can prosper.

iii) The JD company needs to hire an analytic officer who will utilize their knowledge regarding online retail business and can suggest the ways through which JD company can prosper.

Thus from the above description in this Machine learning assignment, it needs to be concluded that it is important for the JD company to introduce machine learning while conducting online business retailing. At the same time, the company needs to look at the ethical, legal and social issues of machine learning. No doubt, there has been observed massive growth in terms of using artificial intelligence nowadays and more importantly, it is processing at a rapid pace. In this context, it is important for the company to look at the various sides of using machine learning and adapt it accordingly.

Reference List
Bishop, C. M. (2006).Pattern recognition and machine learning.Springer. Jordan, M. I., & Mitchell, T. M. (2015). Machine learning: Trends, perspectives, and prospects. Science, 349(6245), 255-260.

Kotsiantis, S. B., Zaharakis, I., &Pintelas, P. (2007).Supervised machine learning: A review of classification techniques.Emerging artificial intelligence applications in computer engineering, 160, 3-24.

Mahdavinejad, M. S., Rezvan, M., Barekatain, M., Adibi, P., Barnaghi, P., &Sheth, A. P. (2018). Machine learning for Internet of Things data analysis: A survey. Digital Communications and Networks, 4(3), 161-175.

Pannu, A. (2015). Machine learning assignment Artificial intelligence and its application in different areas. Artificial Intelligence, 4(10), 79-84.

Russell, S. J., & Norvig, P. (2016). Artificial intelligence: a modern approach. Malaysia; Pearson Education Limited,.

Veale, M., & Binns, R. (2017). Fairer machine learning in the real world: Mitigating discrimination without collecting sensitive data. Big Data & Society, 4(2), 2053951717743530.

Wuest, T., Weimer, D., Irgens, C., &Thoben, K. D. (2016). Machine learning in manufacturing: advantages, challenges, and applications. Production & Manufacturing Research, 4(1), 23-45.

Zhang, L., Tan, J., Han, D., & Zhu, H. (2017). From machine learning to deep learning: progress in machine intelligence for rational drug discovery. Drug discovery today, 22(11), 1680-1685.


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