Machine Learning Implementation in JD: A Comprehensive Report

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Machine Learning in JD

Contents
Executive Summary.....................................................................................................................................3
Introduction.................................................................................................................................................4
1. Definition of Machine learning................................................................................................................5
Difference and Relationship between Machine learning and Artificial Intelligence....................................5
2. Application of machine learning in the other three industries sectors other than the Retailer sector....6
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..........7
4. Discuss the ethical, legal and social issues about the application of machine learning on online retailer
platforms.....................................................................................................................................................9
Recommendations.....................................................................................................................................10
Conclusion.................................................................................................................................................11
References.................................................................................................................................................12

Executive Summary
The following document has been created to study the implementation of machine learning in an
organization called JD. In the course of this document there will be a brief discussion regarding the
various methodologies that can be used for implementation of the technologies associated with
machine learning in JD and also the advantages and disadvantages that must be kept in mind by an
organization while implementing machine learning would also be discussed in order to have a proper
system that support machine learning. There are various aspects of machine learning that are discussed
in this document such as explaining the manners in which the technologies associated with machine
learning are defined along with the task to differentiate between the technologies such as artificial
intelligence and machine learning, surveying and analyzing the various application of machine learning
in various industries in which there is a scope of implementation of machine learning systems,
investigating and deciding whether it would a good idea to implement the machine learning
technologies and system in JD or not, one of the major aspects that would be discussed in this report
would also be to understand the various legal and ethical issues that are faced by any organization while
implementing the technologies and system that associated with machine learning.

Introduction
Machine learning is the type of systems that are completely based upon the technology of neural
networks which is to make the computer system think and learn like a human brain. The machine
learning system is defined as the type of system that is having the ability to learn to react to a particular
input as per the information was given by the user as well as according to the previous inputs and
outputs that are stored in their database. It can be explained as a technology that is evolved by itself
with the help of analyzing and recognizing patterns provided by the developer as well as the user of the
system. It is completely based upon the computational theory that is defined in artificial intelligence.
Machine learning is a technology that provides a computer system the ability to learn by itself and
without being programmed externally or additionally by the user. It is known to be a technology that is
having the ability to handle the data that is provided by it more efficiently. The main purpose of that
machine learning system is to learn from the data that is provided to it by the user or the developer or
even the results that are given by itself to some input.

1. Definition of Machine learning.
Machine learning is defined as the application of artificial intelligence which is mainly used to perform
all the actions of the humans through the machine without being programmed. This technology consist
of various applications through the life of humans has become so easy that they are performing their
daily operation with the help of machine learning. This term machine learning has been derived from
the field of computer science and has many of the uses in the daily life of humans (Soni, et.al. 2019).
This is also used by many organizations as this is beneficial for the firm to attain its goals and objectives
in an effective manner and by reducing human efforts. JD is the Australian online retailer company that
wants to implement the concept of machine learning and artificial intelligence in their organization.
Machine learning comprises of different areas in which they can play the most important role.
The artificial intelligence is related to machine learning which stated that machines can perform all the
operations of humans and also having the ability to act and behave like humans and each and
everything which humans can do and easily complete all of their tasks. Many issues can resolve by the
use of machine learning. The complex and difficult task can also be completed by the use of machine
learning (Lemley, et.al. 2017). The languages which are to be used to solve the difficult problems are
named as ELM, Java, Octave, etc. There are many sectors in which machine learning is beneficial in
different ways. The use of machine learning in healthcare can save the life of humans and can also assist
to recognize the condition of the humans and can describe the prescription of the patient on the live
chat and video calls. The machine learning is also beneficial in the marketing and sales field in which
productivity and profitability can be increased by the use of machine learning. Machine learning
technology is having that much capability that this can handle the multidimensional activities at the
similar time. In business, machine learning can be used to make the best decision for the betterment of
the business enterprise like JD so that they can make better and positive strategies for the firm which
must be effective in nature and aids to gain the satisfaction of customers. JD wants to provide their
customers with such a benefit that the users can be able to visit their online store at any time.
Difference and Relationship between Machine learning and Artificial Intelligence
Both of the terms are substitutable of each other as these are the terms derived from the field of big
data (Soni, et.al. 2019). Artificial intelligence and machine learning are not similar terms but they act to
be similar and this is very necessary to gain knowledge about the difference and relationship between
both terms.
Machine Learning Artificial intelligence
In this technology, access is given to the
machines to learn about everything and access
the data on their own.
This technology defines the use of a machine
to act like humans and complete the entire task
vigorously and effectively.
This technology does not take care of the
success and focuses to increase accuracy.
This technology mainly focuses to attain
success without having the enhancement
inaccuracy.
This technology mainly result in increases the This technology is used to attain understanding

knowledge and intelligence.
2. Application of machine learning in the other three industries sectors other than the
Retailer sector.
There are various sectors where machine learning is helpful and the industries other than the retail
sector are mentioned below -
 Marketing and Sales industry - This is the industry which is mainly assists to be in touch with the
customers and provide them the better services just to gain their satisfaction. machine-learning
will foresee the records of the customers and then recognize that the customers are fond of
which product and then they will suggest or recommend them about their previous product if
they are having the requirement to buy it again and machine learning also helps the customers
to and into their cart which they want to purchase.
 Healthcare Industry - This technology is so much beneficial for the healthcare industry has the
machines of artificial intelligence or machine learning helps analyze cancer, brain tumor and
many of the diseases in an individual (Akella, 2015). The sensors of machine learning are
wearable to human which will assist in ascertaining their present condition and if anything
happens to the patient then that sensor is responsible to depict the situation to the medical
doctor so that the proper treatment should be provided to the patient.
 Finance Industry - This is the industry that deals in finance and must take care of the fraud and
thefts which are harming the industry. Machine learning also recognizes the pattern of the data
in the finance industry and this assists to prevent fraud and protects the company the illegal
things (Soni, et.al. 2019).

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.
The following are the approaches and concepts by using which machine learning can be implemented in
JD organization.
1. Knowing the ways in which Machine Learning can be beneficial for the organization: While
deciding the departments of the organization JD must know the impacts that machine learning
might have on those departments and it must be made sure that there is no department in
which machine learning is being implemented in which there is no need of it in order to save the
wastage of resources and money. The employees of the organization must also be trained for
working with the systems that use machine learning so that when the system is actually
implemented there is no problem for the employees who are working in JD in using those
systems. It must be made sure by JD that all the employees are having an idea regarding the
introduction of machine learning.
2. Analyzing the businesses that are already having machine learning implemented in them: In
order to know the proper implementation of machine learning the organization must make sure
that they are having the idea of an organization that is working in the same domain in which the
organization is working and have already implemented machine learning. By having this
knowledge it would be easier for the organization to figure out the departments in which the
machine learning systems are actually needed and also JD might get some idea regarding the
issues and risks that they might face at the time of the implementation of the same.
Business Functional Area 1: Sales
The selection of the correct platform is highly important for JD if they want to increase there
sales and also implement the systems for machine learning in their organization. There are
various platforms in the market that can be used for the implementation of machine learning
such as Amazon, Baidu, Google, Microsoft, IBM, etc. Almost most of them are priced similarly so
the price comparison cannot be done in this case but still there are a few things that are
required to be kept in mind while choosing the platform implementation of machine learning
such as the special features that these platforms are having and then they must be chosen as
per the requirement of JD. A correct platform would highly affect the sales of the product that is
being launched or sell by JD as the platform that are present in machine learning vary as per the
requirement of the organization and are very much important to be understood that what
would be the platform that might help in proper sales of the services that are provided to the
organization
Business Functional Area 2: Marketing
The proper planning is always needed in order to market the product that has been launched or
to be launched by JD. It must also be must be done before the actual implementation of
machine learning in JD and this plan must answer all the questions that might be asked while
implementing the system related to the implementation of the organization. These questions

might include the name of the departments in which the technology has to be implemented, the
time that it might take for the implementation, the cost that JD might have to spend for the
whole implementation of machine learning in the organization. If all the questions are properly
answered then, in that case, there would be a proper implementation of machine learning in JD.
The marketing process is one of the major characteristics that are seen in any platform while
deciding whether or not to use the particular platform in order to market the services that are
provided by the organization.
The following are the advantages and disadvantages of machine learning.
Advantages
1. It easily identifies and determines the current trends as well as similar patterns
2. There is no actual intervention of any human source needed in it
3. It improves itself with time as it learns more
4. It can also handle that data that is multi-dimensional as well as a multi-variety
Disadvantage
1. It has a known issue of data acquisition
2. There is a lot of wastage of time as well resource while its implementation
3. The possibility of errors in machine learning is very high
4. There might be instances of unexpected results provided by the system.
3.

4. Discuss the ethical, legal and social issues about the application of machine learning on
online retailer platforms.
There are various legal as well as ethical issues that might occur while the implementation of machine
learning in JD which must be kept in mind.
1. The technologies that are related to machine learning are known to be growing at a very high
speed which is a very good thing, but there are various instances that this becomes problematic
in the legal proceedings, there are various rules and norms that are set by the government that
limits the usage of such technologies that are updated frequently, but due to the growing speed
of these technologies there is an issue for the government as they have to keep updating the
norms as per the new technologies are introduced which make this task a very difficult one. If a
legal regulation has been broken by the latest technology that has not been defined by the
government then, in that case, it is difficult for the government to past a just verdict.
2. If there is an accident that involved the technology of machine learning then it is very difficult to
find out who would be at the faulty end, would it be the user who was using the technology? or
would it be the organization that develops the particular application that was involved in the
accident? Or would it be the developer who was responsible for developing the application that
was involved in the accident that took place? JD must be having clear regulation for such policies
and it must be clearly stated in the policies of JD who would be blamed in this case in such
scenarios.
3. The privacy has always been a legal issues in anything that involves a large amount of data over
the internet and in the case of machine learning it has been a very big issue as it can never be
said that the system that has been implemented for machine learning is totally secure and
hence attacks and spoofs would always be involved in these situations.
Solutions
1. In order to solve the issues that are mentioned above, it must be taken care of by JD that
policies that they create for the implementation of machine learning must very clear about each
and every case scenario that might occur in the machine learning system.
2. The applications that are used by JD in order to secure the machine learning systems that are
implemented in the organization, from external attacks, phishes, and spoofs, must be updated
frequently as the latest updates of these kinds of applications are having the ability to prevent
the systems over which they are installed, from the latest types of, malware, attacks, and
phishes that might not be present in the database of the older version of the application.
3. Another thing that must be kept in mind while implementing machine learning in JD is that it
must be made sure that all the employees who are going to use the systems to which machine
learning would be implemented are well trained with the systems before the implementation so
that they do not feel any issue while using them after they are implemented.

Recommendations
With the evaluation of the above report, some of the recommendations are to be suggested to the JD
Company for the progress of the firm and these are mentioned below -
 JD must define the effective business strategies for the improvement of the organization and if
the strategies are not enough to work properly then the concept of machine learning must be
adopted on the subjective view to increasing the growth of the business.
 JD should implement the machine learning and artificial intelligence concept so that the
employees can work accordingly as this reduces the efforts of humans.
 JD can also take the use of reports to make their financial budget and also to explain better the
conditions and growth of the business, JD can take the use of charts and pattern ton to explain
the employees in a better way and define all the outcomes and depicts the result in a positive
way.

Conclusion
The above document that has been created as discussed some of the major aspects of Machine
Learning, in the course of the report it is tried to make the learning understand that artificial intelligence
and machine learning are not exactly similar to each other and a key difference between both the
technologies are also explained. The basic advantages and disadvantages of implementing machine
learning in an organization are also discussed so that it can be kept in mind while doing the
implementation of machine learning systems in JD.

References
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Lemley, J., Bazrafkan, S., & Corcoran, P. (2017). Deep Learning for Consumer Devices and Services:
Pushing the limits for machine learning, artificial intelligence, and computer vision. IEEE Consumer
Electronics Magazine, 6(2), 48-56
Soni, N., Sharma, E. K., Singh, N., & Kapoor, A. (2019). Impact of Artificial Intelligence on Businesses:
from Research, Innovation, Market Deployment to Future Shifts in Business Models. arXiv preprint
arXiv:1905.02092.
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5-easy-steps-to-get-implement-machine-learning-and-artificial-intelligence-in-your-organization.
Artificial Intelligence, (2018). How to make AI work for your organization. Latent View. Retrieved from:
https://www.latentview.com/blog/business-benefit-from-ai/.
Dataflair, (2018). Advantages and Disadvantages of Machine Learning Language. Data Flair. Retrieved
from: https://data-flair.training/blogs/advantages-and-disadvantages-of-machine-learning
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https://www.traverselegal.com/blog/top-5-legal-issues-inherent-in-ai-and-machine-learning/