1. Introduction to Machine Learning 1.1 GeneralIntroduction Machine learning is the sub field of computerscience that is being continuously developed from traditional era to modernera.
In past computer algorithms used to be explicitly programmed which was used bythe computer to solve or calculate the given problem. But now day’s machinelearning algorithms instead allows the computer to train on past data toimprove its result or solution for the given task. (Tagliaferri, 2017/9/28)Algorithms are often elegant and incredibly useful tools used toaccomplish tasks. They are mostly invisible aids, augmenting human lives inincreasingly incredible ways. However, sometimes the application of algorithmscreated with good intentions leads to unintended consequences. It can also becalled as encapsulation.
(Ranie, 2017) Machine learning is also the field of computerscience that has the ability to learn by itself without being programmedclearly or in a detailed way. The trend of Machine learning in computer scienceis growing significantly now days. (Tagliaferri, 2017/9/28)In 1950 a man named Alanturning created the “Turing test”.
Which was able to determine if the computerhas a real intelligence. In 1952 for the very first-time computer learningprogram was written by Arthur Samuel and the name of the program was the gameof checkers. In this program, the more user used to play the game computer usedto improve at the game by studying which moves made up winning strategies andincorporating those moves into its program. (Marr, 2016) 1.
2Current scenariooverview Machine learning is becoming adominant field of computer science so, machine learning is the future of computerscience which must be learned by today’s generation people in order to bringdramatic revolution in field of computer science. As this is the age of bigdata machine learning is being used in various field of science, from astronomyto biology as well as in everyday life of people, as we use digital devicesmore data is continuously being generated and collected as well. Those data maynot be of any use to many people but, some smart people find new ways to usethat 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 2.1Elaboration In today’s world, Machinelearning is used by many companies and industries due to its ability which letscomputer perform the given task more quickly than human could do without beingdirectly programmed to do curtain task, according to nivem Singh, the programand community manager for intels student program for AI part of the intelnirvana Al. academy, the program show cases innovative work done by students atuniversities around the world. (Gilbert, 2017)Machine learning has changedthe way that technology used to perform given task. For example, let usconsider a supermarket that has a huge showroom for all kinds of goods. Thosegoods are sold to millions of customers all around the world. So, every daythere 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 workand that satisfy their needs. Whereas owner of the supermarket wants toincrease the profit and sales of the goods by predicting customers need anddemand which is about next to impossible without machine learning. So, to solvethis 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 lookingfor, what they bought. Analyzing such data helps us understand the process andwe can predict what customer will buy or interested in that helps the owner tomaximize the sales and profit as well. (Alpaydin, 2014/8/22) There are some of thereal-world application of machine learning that is already used in real lifethey are:i.
Speech recognition:Today’s Speech recognition is in more practicethen before. Speech recognition enables the recognition of spoken language intotext form by computers, which uses machine learning in order to train thesystem to recognize speech. Because there is a high rate of an accurate resultwhen the system is trained rather than the untrained system. ii. Computer vision:Some of the computer vision that is developedby using machine learning are face recognition system and system that classifymicroscope images of cells automatically. For example in us more than 85% ofthe handwritten emails are arranged automatically, using trained software thatuses machine learning.
iii. Bio surveillance:Machine learning is playing a very importantrole in detection the diseases. For example, the project called RODS collectsthe data of admission reports to emergency rooms across western Pennsylvania,and with the use of machine learning software the data of admitted patients areanalyzed in order to detect the symptoms for a particular patients diseases andtheir geographical distribution. Some current work involves adding of data ofpurchased medicine in medical stores to improve the machine learning system. iv. Robot control:Machine learning is wildly used in robots especially toacquire control strategies. For example, there was a completion calledDarpa-sponsored that involved 100 miles running race in the desert which waswon by a Robert that used machine learning in which Robert self-collected thedata and used it in detecting the distance objects due to which Robert was ableto win.
(Mitchell, 2006) 3. Implementation 3.1Idea Quality My idea for machine learningis to bring revolution in the field of marketing in Nepal. Machine learning is anew trend in the computer system that is being wildly used by many companies inorder to achieve their goals. So implementing machine learning in Nepal will bedifficult as well as challenging. However, once we are able to implement itthen it will totally change the way we do marketing. As I said before machinelearning can predict future by analyzing past data so we can predict whatcustomer is willing to buy or interested in which results as an improvement inthe sales of goods and profit. 3.
2Plan of the implementation I am planning to implementmachine learning with Chaudhary group (CG) in near coming future. BecauseChaudhary group is one of the leading multination company of Nepal that has 12global partners and associates as well as Chaudhary group is a presence in morethe 20 countries. So with the help of machine learning marketing field ofChaudhary group will get improved significantly in upcoming future. As machinelearning will helps in reducing cost 3.3Technical skills of machine learning i. python:To implement machine learning we require a goodknowledge python.
Python is a programming language has its own role to play inmachine learning. Python contains machine learning algorithm that producescompact and Python programming language courses are available in Nepal.ii. Applied math and algorithms:Math and algorithms play very important role inmachine learning without it machine learning cannot function. Because in orderto function machine learning need curtain algorithms and math that helps tounderstand subject and discriminate models. iii. Distributed computing:Machine learning takes huge number of data setsin order to perform task as it has to analyze past data and improve thealgorithms on its own. Storing huge number of data in a single machine is notpossible so we need different computer in order to process data.
iv. Learning more about advance signal processingtechniques:There are lots of signal processing techniquesnow days some of them are contour lets, shearlets, bandlets which can be usedto solve our problems. (strife, 2015) 3.4Hardware requirement: i. Graphics processing unit(GPU):We require a good Graphics processing unit inorder to perform given task smoothly.
One is GeForce 9000series.ii. Central processing unit(CPU):In order to run machine learning algorithm werequire 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 bechanged 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 thetemperature of computer as computer gets heated during its long time use. If computerget heated more it will effect in its preformation so, cooling is needed.
vi. Power supply:If require high capacity of computers formachine learning so, high power supply is also needed form 1400 watts. (ravankar, 2017) 4. CONCLUSION 4.
1SUMMARY OF KEY FINDING: Simply, the goal of machine learning is to analyzethe certain given data to a computer and improve the given task based on pastexperience that can be understood and utilized by people. (Alpaydin, 2014/8/22) Machine learning has become more popular fromrecent year even though it was started in late 90s. But, still very few companyuses it to improve their company sales while other are planning to implement.It is being continuously being innovated. 4.
2FUTURE ESCALATION: Innear future every task done in industries will be done using machine.Industries must use machine learning in order to be in the marketing race withother 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 likelyto be widely implemented in most of fields with in computer science. Mostly inmarketing field due because it it eliminates business marketing’s greatestenemy, brings real time to life, it reduces costs and help to structuremarketing content. (Samuelson, 2017)