1. becoming a dominant field of a

1. Introduction to Machine Learning

 

1.1 General Introduction

Machine learning is the field in 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 computer to train on data to improve its performance or solution for the given task. Machine learning is also the field of computer science that has ability to learn by itself without being programmed clearly or in detailed way. The trend of Machine learning in computer science is growing significantly now days.  (Tagliaferri, 2017/9/28)

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)

 In 1950 a man named Alan turning created the “Turing test”. Which was able to determine if 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 a 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 finds a 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 has changed the way that technology used to perform given task. For example, let us consider a supermarket that has 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 are stored in computer. In supermarket customer wants to find the goods in 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 computer, which we don’t have. But, supermarket have 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 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 are already used in real life they are:

i.              Speech recognition:

Now days 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 high rate of accurate result when system is trained rather than untrained system.

 

ii.            Computer vision:

Some of the computer vision that are 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 hand written mails are arranged automatically, using trained software that uses machine learning.

 

iii.           Bio-surveillance:

Machine learning is playing 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 specially 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.

 

v.            Accelerating empirical sciences:

Machine learning is changing the way of many data-intensive empirical sciences. For example machine learning is used to analyze the gene of particular person to discover unusual astronomical objects by collecting massive data by the Sloan sky survey to characterize the complex patterns of brain activation that indicate different cognitive states of people in FMRI scanners. (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 new trend in computer system that is being wildly used my 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 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 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.              java/c++/python:

To implement machine learning we require good knowledge of java/python/c++. Each of this programming language has its own role to play in machine learning. Java helps in compiling/debugging, c++ helps in speeding cod up and python contains machine learning algorithm that produce compact. And all of these 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. 

 

3.4 Hardware requirement:

i.              Graphics processing unit(GPU):

We require a good Graphics processing unit in order to perform given task smoothly. Some of the Graphics processing unit are GeForce 9000series, GeForce 10series etc.

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. If we require highest cup then we there is core i9 as well which is latest one.

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:

If we have SSH hard disk it is good because it is faster than HHD but if we have HHD one there should be lots of space. For HHD 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 to 1600 watts.