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Hello My Friends,
How are you all?
This time I am here with a new topic and want to give you some more exiting thing...
Now a day we hear a word Machine Learning majority of times, even when we read any article related to AI. So, I thought this time let me represent Machine Learning in front of you.
Actually, Machine Learning is derived from Artificial Intelligence. We can say like Machine Learning is a child of Artificial Intelligence. Machine Learning means machine can be learning without program. i.e. Machine has to learn.
Now we have a question, Why Machine need to learn?
As a human being, we need to learn something regularly to update and upgrade ourselves, same as machine also has to learn to be upgraded. Because as technology grooves, Machine becomes older, so if machine can learn on it's own, it will be beneficial for it.
Applications for Machine Learning
There are lots of Applications available for Machine Learning such as, Bioinformatics, Search Engines, Speech Recognition, Software Engineering, Game Playing etc.
How are you all?
This time I am here with a new topic and want to give you some more exiting thing...
Now a day we hear a word Machine Learning majority of times, even when we read any article related to AI. So, I thought this time let me represent Machine Learning in front of you.
Actually, Machine Learning is derived from Artificial Intelligence. We can say like Machine Learning is a child of Artificial Intelligence. Machine Learning means machine can be learning without program. i.e. Machine has to learn.
Now we have a question, Why Machine need to learn?
As a human being, we need to learn something regularly to update and upgrade ourselves, same as machine also has to learn to be upgraded. Because as technology grooves, Machine becomes older, so if machine can learn on it's own, it will be beneficial for it.
Applications for Machine Learning
There are lots of Applications available for Machine Learning such as, Bioinformatics, Search Engines, Speech Recognition, Software Engineering, Game Playing etc.
How to Work with Machine Learning?
First of all for machine learning there are lots of algorithms available for different modules and even we have lots of programming languages such as, Java, Python, R etc. we can work for machine learning using these languages. But the thing is How? Because there are lots of programming languages available and we have already known these different languages but with Machine Learning? So, for Machine Learning there are lots of libraries or modules or library packages available using these libraries we can work with any language for Machine Learning Algorithm.
So, if you can work with Java, you have different types of libraries available such as, DL4J, Weka, Massive Online Analysis (MOA), Mallet etc.
Weka
Weka is GUI library for java. and generally used for data mining and analysis. it's strength lies in classification of data, clustering, association rule etc.
Massive Online Analysis(MOA)
MOA is used for data mining like weka. even we can combine these both weka and MOA. MOA is used for classification, regression, clustering etc.
DeepLearning4J
This library is specially designed for Deep Learning. It is used for commercial purpose and it is open source library. It is used for different patterns.It also works for Scala and it is super power for deep neural network and reinforcement.
Mallet
It is another Java based open source library for natural language processing. and it also supports lots of different types of algorithms. such as, Naive Bayes, Decision Tree etc.
If you are a master in Python, you have Tensorflow, Scikit - learn, Pylearn2, NuPic like modules, using these modules you can work with Machine Learning.
R is also used with Machine Larning, we have lots of libraries available such as, e1017, rpart, nnet, tree etc.
Even we have lots of other languages, using these languages we can work with Machine Learning such scala, clojure etc. even C++ like languages also support Machine Learning.
This is just a brief introduction of Machine Learning, and how to work with Machine Learning in Java and other languages. such as, Python and R. using different libraries and modules.
In next article of Machine Learning, I will be there with some new information related to ML.
Till then, Friends enjoy with Machine Learning.
So, if you can work with Java, you have different types of libraries available such as, DL4J, Weka, Massive Online Analysis (MOA), Mallet etc.
Weka
Weka is GUI library for java. and generally used for data mining and analysis. it's strength lies in classification of data, clustering, association rule etc.
Massive Online Analysis(MOA)
MOA is used for data mining like weka. even we can combine these both weka and MOA. MOA is used for classification, regression, clustering etc.
DeepLearning4J
This library is specially designed for Deep Learning. It is used for commercial purpose and it is open source library. It is used for different patterns.It also works for Scala and it is super power for deep neural network and reinforcement.
Mallet
It is another Java based open source library for natural language processing. and it also supports lots of different types of algorithms. such as, Naive Bayes, Decision Tree etc.
If you are a master in Python, you have Tensorflow, Scikit - learn, Pylearn2, NuPic like modules, using these modules you can work with Machine Learning.
Tensorflow
This module is used for high level neural network. It helps
you to work with CPU or GPU. It mainly written in C++.
SciKit – learn
This python module is generally used to analyze and mine data. It builds by using NumPy, SciPy and matplotlib.
Pylearn2
This module is used for neural network. But it also work with other libraries i.e. we can combine other libraries with Pylearn2.
NuPic
This module does not work only for ML algorithms but it has some other functionality. It works with hierarchical temporal memory (HTM) is available in neural network. So, we can see it's powerful side.
R is also used with Machine Larning, we have lots of libraries available such as, e1017, rpart, nnet, tree etc.
e1071
This package is used for fuzzy clustering, support vector machine, shortest path problem etc types of ML algorithms.
rpart
This package is used for recursive partitioning and regression trees type of machine learning algorithms.
nnet
This library package is used for Neural Network and log linear models in ML.
tree
As the name suggest, this library package is used for classification tree and regression tree.
Even we have lots of other languages, using these languages we can work with Machine Learning such scala, clojure etc. even C++ like languages also support Machine Learning.
This is just a brief introduction of Machine Learning, and how to work with Machine Learning in Java and other languages. such as, Python and R. using different libraries and modules.
In next article of Machine Learning, I will be there with some new information related to ML.
Till then, Friends enjoy with Machine Learning.
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