If you look around yourself , You will find intelligent people around you . That is not strange but If I say Machines around you are also intelligent ? Its not funny and I am not joking .Machine are learning and their learning speed is quite faster than humans. You are thinking how this magic is possible Right ? Your expressions are indicating me that I am in Right Direction. Anyways All this is because of Powerful Machine Learning Library .
In this Article We will explore Top 5 Machine Learning Library is Python . These Libraries may help you to design powerful Machine Learning Application in python . These Machine Learning Libraries in Python are highly performance centered . You can directly import in your application and feel the magic of AI . I have not ranked them only on the basis of their functional capability but also I considered their user documentation. Every Machine Learning Library must contain certain information in their documentation like data set format compatibility , Data set sources etc.
If you need a background overview of machine learning you can refer our article What is Machine Learning ?
Top 5 Machine Learning Library in Python
It is new neural Network API . Let me tell you a interesting fact about it . There was a time when Google Inc . ,were busy in developing Google Brain . The Team of Google realized need for a complete machine learning library on neural network . This is how TensorFlow born . Anyways Lets move towards its features It has flexible Architecture. So you can deploy it on distributed Architecture system on parallel processing as well as single CPU system. Major part of TensorFlow is on C++ with upper binding on Python.
You can download and access TensorFlow from here .
2. SciKit-learn –
SciKit-learn python API is one of the most popular Machine Learning Library . It is too popular because It covers basic library of python like NumPy, SciPy and Matplotlib . These three library is most important when you are dealing with data science / Machine Learning /AI . This integration give quite familiar feeling to developer writing Machine Learning Code .
You can use and understand SciKit-learn from here. This library covers almost every thing which a Data Scientist requires .
Theano is another big name in the world of Python data science. It is quite similar to SciKit Machine Learning Library . It has also built over NumPy . This gives massive control over Mathematics expression. If we talk about data structure handling , it has awesome features . Specially in Multi Dimensional array , It is far better than others Machine Learning Library . Installation is quite easier because of clear GPU ARCHITECTURE.
For more understanding in Theano Machine Learning Library , You can refer official website of Theano. Developer use Theano for Deep Learning Application/Model.
4.Pylearn 2 Machine Learning Library-
It is just a wrapper of Theano . I am going to tell you a beautiful usecase of this Machine Learning Library . When ever you do not want to customize too much in existing model code. You just want to use existing functionality under existing API . Pylearn 2 will be the best solution for you . You can customize the code but there will be limitations . One more thing , I would Like to add is , ” Starter version of Pylearn 2 has few bugs but so many bugs has been resolved by great community support” . But still , Be careful to use it .
If you need more information over Pylearn 2 and you want to import it . just Click on Pylearn2.This machine learning library is mostly useful in Deep Learning.
5. Other Basket of machine learning library-
Apart from above mentioned libraries , There so may useful machine learning library in python . I am not going to deep in each I will only list the name of them . You can click over their name and can reach their official website . These above written were primarily used machine learning libraries in python . You can do most of the task( Machine Learning ) by using one them . Still this basket is important . The list is here –
I think , I have mentioned most of the important and useful Machine Learning library of python . Apart from these there are so many others libraries . If you need any other information , you can comment or write back to us . Our Team will help you as soon as possible .
Anyways Lets talk about the performance of these machine learning libraries. If you import these libraries as black box model . The complexity of your Application will depend how you call these API . In case you are customizing these API and using these Machine Learning Model as white box . Then in that case , These will be two factors how did you call these API and how did you customize the functions written in these libraries . So be smart while using these API . It will be quite risky to use the model blindly for performance related issue .
What Else is required ?
These Machine Learning Libraries are in Python .I will suggest you to take overview of python . If you want to quick revise or learn python essentials .You can refer our article Learn Python essentials in 5 Minutes .
Still If you have doubt in your mind why we should use python for data analysis . The article complete overview of python for data analysis will clear all your queries . In fact along with python , what other skills are required to become a full stack Data Scientist are also mention in our article How to become a Data Scientist – complete Guide .
Like Python , There are tremendous API of Machine Learning are available in java and other programming languages. Some of us call these Machine Learning library by the name of Machine Learning Framework .In General both are similer but in deep context there are so many difference . I will not speak much about it in this post except ,” when the flow of control added with library then it become a framework “.
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Data Science Learner Team
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