Big Data Machine Learning
Big data machine learning
Currently,we have ability to do store and processing large amount of data as well as to acess it from physically distant locations over computer network.Most data acquistion devices are digital now and record reliable data.For example,take supermarket chain that has hundreds of stores all over a country selling thousands of goods to millinons of customers.
The pont of scale terminals record details of each transcation:date,customer identification code,goods boughts and their amount,total money spent ..etc,This typically amounts to gigabytes of data everyday.This stored data becomes useful only when it is analyzed and turned into information that we can make use of to make predications.
we dont know which customer brought a particular item,it is very difficult to identify.we would just go write code for that,but because we do not,we can only collect data and hope to extract the answers to these and similar questions from data.
we are not able able to identify the process completely,but we can construct a good and useful approximation,that approximation may not give explain everything.we may not able to identify the complete process,we can still detect certain patterns or regularities.This is niche of machine learning,such patterns may help to identify the process and use those patterns may able to make predictions:Assuming that the future,atleast the near future.
Big data Machine learning is programming computers to optimize a performance criteria using example past data.we have define amodel have up to some parameters and learing is the execution of compuetr program to optimize the parameters of the model using training data(past data).Big data Machine learning uses the theory of statistics in buliding mathematics models.
Big data machine learning
Applications of Big data Machine Learning:
Finance banks(detect faurd detection)
WWW(world wide web)…etc.,
But Machine learning is not a just database problem,it is part of artificial intelligence.To be intelligent,a sytem that is in a changing environment shpold have ability to learn.Machine learning also helps us to find solutions to many problems in vision,speech recognition and robotics.
Examples of Big data Machine Learning Applications:
In retail application,take supermarket chain-one of the application of machine learning is basket analysis,which finding assocations between products broughts by customer.If people who buy products x also typically buy products y and if there is customer who buy x and does not buy y,he or she is potential y customer,once we finding such customers ,we can target them for cross-selling.
Let take an example,customer who want to apply bank loan.Bankers should check the details of customer,whether person is applicable to this loan.This is example of classification problem where there are two class:low risks customers and high risks customers.The information about customer makes up the input to the classifier whose task is to assign the input to one of the two classes.
Let us say we want to have a system that can predict the price of used car.car has some properities such as engine capacity,brand ,year,milage..etc,this are input of car attributes to find the cost of used car.such problems where output is animber are regression problems.
In supervised Learing, to learn a mappinng from input to output whose correct values are provided by supervisior.In unsupervised learning doest have supervisor for giving values.The aim to find the regularities in the input.
In some applications,the output of system is a sequence of actions.single action is not enough.what is important is the policy that is the sequence of correct actions to reach the goal.A good example is game playing.game playing is an important reasearch area in both artificial intelligence and machine learning.Another example is robot navigation.
Big data machine learning which have lot of algorithms to solving real time problems.Big data machine learning which may help able to make future predictions in any applications