Implementation of Machine Learning in E-commerce: A Case Study of JD Company

Running head: IMPLEMENTATION OF MACHINE LEARNING
IMPLEMENTATION OF MACHINE LEARNING
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IMPLEMENTATION OF MACHINE LEARNING
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Executive summary:
This report is about implementation of the machine learning in an online retail company
of Australia, JD Company. The brief concept of the machine learning is provided for better
knowledge of the machine learning in the ecommerce field and how it is different from the
Artificial intelligence is discussed. The advantages and the disadvantages of Machine Learning
in the industry is discussed in the report. There are certain issues that arises when a new system
is implemented which is also discussed in brief along with some recommendations for the
improvement of the system.

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Table of Contents
Introduction to Machine Learning...................................................................................................3
Application of Machine Learning in different industry...................................................................5
Machine Learning in Transportation...........................................................................................5
Machine Learning in Healthcare.................................................................................................6
Machine Learning in Media.........................................................................................................6
Implementation of Machine Learning in JD:...................................................................................7
Advantages of ML in E-commerce:........................................................................................7
Disadvantages:.........................................................................................................................8
Ethical legal and social issues of application of the machine learning........................................9
Conclusion.....................................................................................................................................10
Recommendations..........................................................................................................................10
References:....................................................................................................................................12

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Introduction to Machine Learning:
System’s ability to learn automatically and improvise from the previously performed task
without being programmed explicitly to do so is known as machine learning. It is an application
based on the Artificial Intelligence. The primary focus of the Machine Earning is to improve the
performance of the computer organs and develop them, especially those which can access the
data and make better use of the information and learn from there. There are program which
observes the activities and the data such as the orders and experiences that are performed
repetitively on the system (Nair, Umamaheswari & Kuppusamy, 2016). The goal of
implementing the Machine Learning in the computer system was to let the computers learn by
themselves automatically and to some extent it is a success.
There are a certain methods which are followed by machine learning. They are discussed
as follows:
Supervised Algorithms for Machine Learning: The lessons learnt from the past,
mainly form the labelled examples, is used in the present and is also used for predicting the
future events in the system. The algorithm analysing the pre-existing training data-set and a
function is developed for which predicts the probable outputs (Anandakumar & Umamaheswari,
2017). After a certain amount of training is applied on the system, the system is capable of
providing target to any input that is given to the system.
Unsupervised Algorithms for Machine Learning: unlike the supervised algorithms, the
unsupervised algorithms are used when the example used for the training are not completely
classified or labelled. This algorithm checks the system’s ability to understand any hidden