1. it into a useful product or service.

1. Introduction to Machine Learning

 

1.1  General
Introduction

 

Machine learning is the sub field of computer
science that is being continuously developed from traditional era to modern
era.
In past computer algorithms used to be explicitly programmed which was used by
the computer to solve or calculate the given problem. But now day’s machine
learning algorithms instead allows the computer to train on past data to
improve its result or solution for the given task. (Tagliaferri,
2017/9/28)

Algorithms are often elegant and incredibly useful tools used to
accomplish tasks. They are mostly invisible aids, augmenting human lives in
increasingly incredible ways. However, sometimes the application of algorithms
created with good intentions leads to unintended consequences. It can also be
called as encapsulation. (Ranie, 2017)

 Machine learning is also the field of computer
science that has the ability to learn by itself without being programmed
clearly or in a detailed way. The trend of Machine learning in computer science
is growing significantly now days.  (Tagliaferri, 2017/9/28)

In 1950 a man named Alan
turning created the “Turing test”. Which was able to determine if the computer
has a real intelligence. In 1952 for the very first-time computer learning
program was written by Arthur Samuel and the name of the program was the game
of checkers. In this program, the more user used to play the game computer used
to improve at the game by studying which moves made up winning strategies and
incorporating those moves into its program. (Marr, 2016)

 

1.2
Current scenariooverview

 

Machine learning is becoming a
dominant field of computer science so, machine learning is the future of computer
science which must be learned by today’s generation people in order to bring
dramatic revolution in field of computer science. As this is the age of big
data machine learning is being used in various field of science, from astronomy
to biology as well as in everyday life of people, as we use digital devices
more data is continuously being generated and collected as well. Those data may
not be of any use to many people but, some smart people find new ways to use
that data and turns it into a useful product or service. In this transformation,
machine learning plays a huge role. (Alpaydin, 2014/8/22)

 

2. Background

 

2.1
Elaboration

 

In today’s world, Machine
learning is used by many companies and industries due to its ability which lets
computer perform the given task more quickly than human could do without being
directly programmed to do curtain task, according to nivem Singh, the program
and community manager for intels student program for AI part of the intel
nirvana Al. academy, the program show cases innovative work done by students at
universities around the world. (Gilbert, 2017)

Machine learning has changed
the way that technology used to perform given task. For example, let us
consider a supermarket that has a huge showroom for all kinds of goods. Those
goods are sold to millions of customers all around the world. So, every day
there is a huge transaction that is stored in the computer. In supermarket,
customer wants to find the goods in a cozy way that suits them or their work
and that satisfy their needs. Whereas owner of the supermarket wants to
increase the profit and sales of the goods by predicting customers need and
demand which is about next to impossible without machine learning. So, to solve
this problem we need an algorithm to run in the computer, which we don’t have.
But, supermarket has data of every customer like what customers were looking
for, what they bought. Analyzing such data helps us understand the process and
we can predict what customer will buy or interested in that helps the owner to
maximize the sales and profit as well. (Alpaydin, 2014/8/22)

 

 

There are some of the
real-world application of machine learning that is already used in real life
they are:

i.             
Speech recognition:

Today’s Speech recognition is in more practice
then before. Speech recognition enables the recognition of spoken language into
text form by computers, which uses machine learning in order to train the
system to recognize speech. Because there is a high rate of an accurate result
when the system is trained rather than the untrained system.

 

ii.           
Computer vision:

Some of the computer vision that is developed
by using machine learning are face recognition system and system that classify
microscope images of cells automatically. For example in us more than 85% of
the handwritten emails are arranged automatically, using trained software that
uses machine learning.

 

iii.          
Bio surveillance:

Machine learning is playing a very important
role in detection the diseases. For example, the project called RODS collects
the data of admission reports to emergency rooms across western Pennsylvania,
and with the use of machine learning software the data of admitted patients are
analyzed in order to detect the symptoms for a particular patients diseases and
their geographical distribution. Some current work involves adding of data of
purchased medicine in medical stores to improve the machine learning system.

 

iv.          
Robot control:

Machine learning is wildly used in robots especially to
acquire control strategies. For example, there was a completion called
Darpa-sponsored that involved 100 miles running race in the desert which was
won by a Robert that used machine learning in which Robert self-collected the
data and used it in detecting the distance objects due to which Robert was able
to win. (Mitchell,
2006)

 

3. Implementation

 

3.1
Idea Quality

 

My idea for machine learning
is to bring revolution in the field of marketing in Nepal. Machine learning is a
new trend in the computer system that is being wildly used by many companies in
order to achieve their goals. So implementing machine learning in Nepal will be
difficult as well as challenging. However, once we are able to implement it
then it will totally change the way we do marketing. As I said before machine
learning can predict future by analyzing past data so we can predict what
customer is willing to buy or interested in which results as an improvement in
the sales of goods and profit. 

 

3.2
Plan of the implementation

 

I am planning to implement
machine learning with Chaudhary group (CG) in near coming future. Because
Chaudhary group is one of the leading multination company of Nepal that has 12
global partners and associates as well as Chaudhary group is a presence in more
the 20 countries. So with the help of machine learning marketing field of
Chaudhary group will get improved significantly in upcoming future. As machine
learning will helps in reducing cost 

3.3
Technical skills of machine learning

 

i.             
python:

To implement machine learning we require a good
knowledge python. Python is a programming language has its own role to play in
machine learning. Python contains machine learning algorithm that produces
compact and Python programming language courses are available in Nepal.

ii.           
Applied math and algorithms:

Math and algorithms play very important role in
machine learning without it machine learning cannot function. Because in order
to function machine learning need curtain algorithms and math that helps to
understand subject and discriminate models.

 

iii.          
Distributed computing:

Machine learning takes huge number of data sets
in order to perform task as it has to analyze past data and improve the
algorithms on its own. Storing huge number of data in a single machine is not
possible so we need different computer in order to process data.

 

iv.          
Learning more about advance signal processing
techniques:

There are lots of signal processing techniques
now days some of them are contour lets, shearlets, bandlets which can be used
to solve our problems. (strife, 2015)

 

3.4
Hardware requirement:

 

i.             
Graphics processing unit(GPU):

We require a good Graphics processing unit in
order to perform given task smoothly. One is GeForce 9000series.

ii.           
Central processing unit(CPU):

In order to run machine learning algorithm we
require a high central processing unit like 3.8 GHz with core i7-6850k.

iii.          
System memory:

At least 8 GB of memory is needed which can be
changed later up to 64 GB later in motherboard.

iv.          
Storage:

HHD hard disk at list 1TB is required.

v.           
Cooling:

Cooling computers helps to maintain the
temperature of computer as computer gets heated during its long time use. If computer
get heated more it will effect in its preformation so, cooling is needed.

vi.          
Power supply:

If require high capacity of computers for
machine learning so, high power supply is also needed form 1400 watts. (ravankar, 2017)

 

4. CONCLUSION

 

4.1
SUMMARY OF KEY FINDING:

 

Simply, the goal of machine learning is to analyze
the certain given data to a computer and improve the given task based on past
experience that can be understood and utilized by people. (Alpaydin,
2014/8/22)

 

Machine learning has become more popular from
recent year even though it was started in late 90s. But, still very few company
uses it to improve their company sales while other are planning to implement.
It is being continuously being innovated.

 

4.2
FUTURE ESCALATION:

 

                    

In
near future every task done in industries will be done using machine.
Industries must use machine learning in order to be in the marketing race with
other industries because machine learning is the future of computer science so,
Industries must join the future. (Tank, 2017)

In the near future machine learning is likely
to be widely implemented in most of fields with in computer science. Mostly in
marketing field due because it it eliminates business marketing’s greatest
enemy, brings real time to life, it reduces costs and help to structure
marketing content. (Samuelson, 2017)