Assignment | Machine Learning 2022

minimum 15 references 6 references should be academic CQU library journals and conference proceeding

Running head: COIT20249
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Name of the Student
Name of the University
Author Note

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Executive Summary:
This report aims to discuss various of aspects of the machine learning in the area of online retail
organization. In this aspect JD, which is an Australian online retailer is currently looking for
implementing machine learning within their organization. Thus, in this paper various aspects of
the machine learning has been discussed here. Firstly, this report has discussed about the
machine learning on which the definition of the machine learning has been elaborated and
relationship and differences among the AI and machine learning has been discussed. This report
has also surveyed various of applications of machine learning in the healthcare industry, oil and
gas industry and in the transportation industry. Here, JD can adopt the machine learning
applications which has been also elaborated briefly. Machine learning applications has been
discussed in two diverse business functional areas of JD. Some advantages and disadvantages of
the applications of the machine learning has been discussed in this report. Legal, ethical and
social issues of the machine learning applications on the online retailer platforms has been
discussed in the report. Lastly, in this report recommendations has been made regarding how the
JD can adopt the machine learning within their businesses.

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Table of Contents
Introduction:....................................................................................................................................3
Explanation of the Machine Learning:............................................................................................3
Machine Learning Survey:..............................................................................................................4
Implementation of machine learning:..............................................................................................5
Application of machine learning:....................................................................................................6
Advantages of machine learning.....................................................................................................7
Disadvantages of machine learning.................................................................................................7
Ethical, Legal and Social issues of Machine Learning Applications..............................................8
Recommendations for using machine learning:..............................................................................9
Conclusion:....................................................................................................................................10
References:....................................................................................................................................12

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Introduction:
The machine learning is one of the important and trending topic in the current situation.
The machine learning can be actually considered as scientific study of the statistical models and
the algorithm which is used by the computer systems for execution of a specific type of tasks
without providing any type of external instructions (Witten et al., 2016). For performing the
tasks it actually relies on the interference and on the patterns. The machine learning can be
actually considered as a subset of the artificial intelligence. In the current aspects the JD which is
an online Australian retailer believes that application of the machine learning can improve their
businesses regarding improved customer service.
Depending on this believes in this report a brief discussion regarding the machine
learning will be discussed. Following that in this report machine learning will be surveyed on
three other industries. Following that how JD will be able to adopt the machine learning in their
organization will be evaluated. In the next section social, legal and ethical issues regarding
machine learning applications will be discussed. In the further section of this report
recommendations will be provided regarding how JD will be able to adopt the machine learning
within their businesses.
Explanation of the Machine Learning:
The machine learning is actually particular field of study which provides the computer
system learning capability without being programmed in an explicit manner (Mohri,
Rostamizadeh & Talwalkar, 2018). Currently, the machine learning is one of the exciting
technologies which is dominating the current technological market. In this way, by the
implementation of the machine learning the computers will be able to develop their own

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intelligence and in this way the computer systems will become more likely the humans. In a
specific manner it can be elaborated that machine learning is actually is the learning ability of the
computer systems by their own.
The machine learning is actually a subsection of the artificial intelligence but there are
several of differences among the machine learning and the artificial intelligence. As a subset of
the artificial intelligence there are some relationships are also present. Here the machine learning
resides under one of the broad field of the artificial intelligence and it is the main relation
between the machine learning and the artificial intelligence (Jordan & Mitchell, 2015). The
machine learning is not separated from the artificial intelligence. Thus, the machine learning
cannot be existed without the applications of artificial intelligence. In this aspect the main
dissimilarities among the machine learning and the artificial intelligence is that, AI is decision
making while the machine learning helps the systems to learn new things from the data by their
own. Also, the main target of the AI is increasing the chances of success while machine learning
looks aims for increasing the accuracy.
Machine Learning Survey:
The machine learning can be utilized various of industries other than the online retail
industry. Here the important industries in which the machine learning can be used are the
healthcare industry, transportation industry and oil and gas industries. While considering the
healthcare industry there are several of applications of the machine learning. Currently the
machine learning is used in the wearable sensors and devices which can proactively use the
incoming data from patient’s body for assessing the health condition of the patients in the real
time environment (Chen et al., 2017). In this aspect digital health platform is also implemented
by using the machine learning so that health conditions of the patient can be monitored

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contentiously. The data which is gathered from the body of the patient is directly sent to the
centre of machine learning analytics. From this centre anomalies in the health condition is
flagged out and treatment alert is provided. Improved diagnosis can be also done using the
machine learning applications.
The transportation industry is also influenced by the implementation of the machine
learning. The machine learning is used within transportation industry for data analysis purposes.
In this way the patterns and current trends within the gathered data is discovered within the
transportation industry (Jahangiri & Rakha, 2015). By the identification of those patterns and the
trends transportation industry can become beneficial from it. In this way the routes can be more
efficient and the potential problems can be identified before which will be actually increasing the
profitability.
In the oil and the gas industries this machine learning is having a greater impact. Machine
learning has become an integral part of the most gas and oil companies. Here, machine learning
helps the organizations to gather a huge amount of data and helps to convert this data into some
actionable insights. From this gathered data the organization can be innovative and by the
employment of the machine learning strategies. The machine learning will be boosting the
efficiencies, reducing the costs and improving the safety of this industry which is one of the most
important criteria of this type of industry (Layouni, Hamdi & Tahar, 2017). In this way machine
learning can help the oil and the gas industry.
Implementation of machine learning:
The overall implementation of machine learning follows a number of steps in the
organization of JD. The following steps are:

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Provide Training – To provide the proper knowledge of Artificial Intelligence and also machine
learning (Crawford et al., 2015). Because both the technology relates to each other and help to
produce the maximum outcomes of the organization. So, it must provide the appropriate training
to all the lead engineers of the organizations so that they can understand about the working
principle as well as the benefits of this technology.
Understanding the implementation of machine language – Since, the overall process of
machine language is technical based that’s why it needs to related with the organizational goals
as well as addressing the actual issues.
Selection of right platform – It needs to select the right platform of machine language based the
needs of the organizations (Gupta & Pathak, 2014). Because the technology offers various
individual platforms.
Development of healthy strategy – It needs to maintain as well as follow the rules or controls
related to the machine learning technology that actually relates to the outcomes of the
organizations and increase the customer flow.
Preparation of implementation plan – Before starting the deployment of the outcomes, it needs
to implement a plan regarding machine language at the initial plan. Because the plan induces that
which kind of activities take place to get the actual range of products in the organization.
Application of machine learning:
Here according to the case study, JD wants to build up the customer experiences as well as the
organizational results. The machine learning application on these business functional areas are
such as –

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Customer Experience – As because the machine learning technology allows the e-commerce
business for creating more customer experiences (Milgrom & Tadelis, 2018). This machine
learning provides an ability of personalization of the organization so that the customers can get
as per their requirements. With the increment of customer experience, it helps to increase the
outcomes of the organisation.
Searching the results – Machine learning helps to improve the e-commerce technology for
searching the results at each of the time in which the customer buys the products as per shown in
the purchase history. At the earlier time, the traditional search methods such as keyword
matching for searching the results. But the machine learning technology helps to create a search
ranking that depends on the relevance of the customers.
Advantages of machine learning
The following advantages of machine learning are –
 It does not require to any human intervention in this technology. Because all over the
technology depends on the algorithms which are put in the initial time.
 It helps to improve the organization continuously (Perlich et al., 2014). Because with the
help of machine learning, it needs to increase the customers experience as well as the
productions of the organizations.
Disadvantages of machine learning
The disadvantages of the machine learning are –
Interpretation results – It is concern that the choosing of algorithms is codirect for machine
learning. Because based on the algorithms, the results may be incorrect.

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High error susceptibility – The major drawback of the machine learning is the high error
susceptibility.
Ethical, Legal and Social issues of Machine Learning Applications
The ethical issues related to the machine learning application includes not so much
machine learning algorithms themselves but the way the data is used. The biggest problem is the
data. It perhaps three issues. A good machine learning applications must have a lot of data. It
might be open-sourced data, and it is free (Ashley & Walker, 2013). The information may be
publicly available for a price. Sometimes it may happen that the data might be owned by a group
of people in the online social retailing site of JD. Some intruder can steal the private as well as
sensitive information of the customers. For that reason the customer may feel insure while
accessing the web
There are lots of legal issues in machine learning applications in online retailers’
applications.
 In the accident involves machine learning, the machine learning is trying to detect the
responsible party that is playing a science-fiction version of clue (Di Mauro & Di Sarno,
2014). The machine unable to find that who is responsible for the hacking of a particular
site.
 By using the machine learning-based applications the JD Company will able to track the
prediction of purchase of a person. If that application is hacked then an intruder can
know the prediction details of a particular customer for purchase.
The machine learning applications has its legal obligations in online social retailers’
applications. Data controllers are legally bound to providing automated type of decision making

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process. Here it also places these technologies under a legal spotlight (Landset et al., 2014). It
will assist the authority of JD Company to predict the decision making about the prediction of
customer. The ecommerce expert must be able to elaborate the decision that can affect society.
Recommendations for using machine learning:
The company can use the recommendation engine in its application. With utilization of
machine learning and large amount of data processing the company is able to analyse the activity
of the millions of users in an online environment. On the basis of this, the company is able to
generate the recommendation of the product which is tailored to the specific user or group of
users (Lehr & Ohm, 2017). By analyzing the gathered data on the current traffic on web portal
the company can able to determine the subpages that are used by the client. The company can
able to detect what the customer is trying to find out. Based on the various kinds of information
that the authority can able to detect the activity of the user profile, its preferences, and data of the
social media, location and weather (Li & Chen, 2013). The outcome will be shown on the
personalized page with the recommended items that is more likely attract them.
The JD Company can implement the personalized content within website or in the
applications of mobile so that they can increase the conversion as well as engagement of the
consumer. It can find specific patterns of data on large amount of data processing regarding
structured and unstructured data. Machine learning algorithms are able to implement this kind of
things (Portugal, Alencar & Cowan, 2018). It includes the favourite style, colour, and intensity of
images, history of the activity, preferences and many others. The outcomes regarding website are
adapted to the personal choices of that person. By using this methodology the company can
increase the revenue.

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The machine learning algorithm can able to use the model the machine learning algorithms
for dynamic pricing (Surden, 2014). This company could profit from the predictive type of
models which will allow them to detect the optimal price for each of the product. The company
can select to use this type of offer for ideal price and view discounts on real time. It is used to
enhance the sales of the company and also optimize the inventory.
A/B tests can able the website to be adapted by the users. Almost eighty per cent of the A/B
tests does not give positive outcomes (Landset et al., 2015). Execution of this process is quite
difficult. The machine learning methods will help the company with:
 Automatic classification of the customer in to the groups by using the unsupervised
machine learning models that depend on the characteristics and the personalization of the
content (Landset et al., 2015). For example, for women aged more than forty, the main
color of the page will consist burgundy while for the males under twenty years old the
color is blue.
 By using the faster discovery of the optimal options of products by using the self-
learning algorithm instead of using the monotonous work (Portugal, Alencar & Cowan,
2018). It also allows retailers in online environment to minimize the orders.
Machine learning is used for performing the prediction of the user in ecommerce. In real time
the seller can able to react consequently. It gives the company the chance to upsurge the
conversations while the user is considering the purchasing activity (Lehr & Ohm, 2017). It can
able to predict whether the user is willing to return and what kind of purchases him or he wants
to make (Li & Chen, 2013). This will assist in matching the correct type of marketing strategy to
that person to rise the future purchase conversation and encourage the person in their returning
process.

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Conclusion:
The above discussion implies that machine learning is one of the most important area in
the field of computer technology. The concept of machine learning can effectively help the
computer systems to become intelligent as this helps to learn them by their own without any type
of external inputs. Computers uses the gathered data in this case for the learning process. In this
report JD, which is an Australian online retailer is looking to implement machine learning
through which their overall business performance can be improved. In this aspect, first of all
definition of the machine learning has been provided and the differences and the relation among
the machine learning and artificial intelligence has been provided. In the following section of this
report the machine learning applications has been surveyed in total three dissimilar industries.
The following section of this report has discussed how JD will be able to adopt the applications
of the machine learning in two diverse types of business functional areas of them. Important
disadvantages and advantages of the application of machine learning has been described here.
There are various of legal, social and ethical issues are related with the machine learning
application on the platform of online retailer which has been discussed here. Further section of
this report has discussed recommendation regarding how JD will be able to adopt the machine
learning.

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processing: A machine-learning approach. In 2014 International Carnahan Conference
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prospects. Science, 349(6245), 255-260.

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Landset, S., Khoshgoftaar, T. M., Richter, A. N., & Hasanin, T. (2015). A survey of open source
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Witten, I. H., Frank, E., Hall, M. A., & Pal, C. J. (2016). Data Mining: Practical machine
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