How to deploy a machine learning apps using Java

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Java Using Machine Learning
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Bright Future of Machine Learning

• If you have good experience in Java programming,
  you must need to get move of this curve now when
  latest innovative consulting are staring to
  seriously invest in machine learning.
• When you startup today, you can increase
  development skill on few some years but must
  start somewhere.

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Java Libraries For Implementing ML

• ADAMS - Advanced Data mining And Machine learning
• Deeplearning4j - Deep Learning for Java
• ELKI
• JavaML - Java Machine Learning
• JSAT - Java Statistical Analysis Tool

DL4J
JavaML
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Java Libraries For Implementing ML

• Mahout - Apache Mahout
• MALLET - Java "Machine Learning for Language
  Toolkit
• MOA - Massive Online Analysis
• RapidMiner
• Weka - Waikato Environment for Knowledge Analysis

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Why Use Java for ML?

• Number of Data is an essential to developing
  machine learning services, Machine learning tools
  require to integrate well with those
  technologies. Machine learning starts with
  collecting data.
• Thats why machine learning driving you select is
  critical. The correct tools solve a lot of
  integration issues and they will boost the
  digital world for businesses.

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Machine Learning Process
Training Data
Validation Data  
Ho(X)
Quality Metrics
Algorithm
Study
Evaluate
Choosing The best      
Ho(X)
Unlabeled Data
Predict Label Y
Predict
Resource by Javaworld.com
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Top 5 Programming Languages For ML
Machine Learning
Python
Java
R
Prolog
Lisp
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ML Frameworks for Java
Apache Singa is a portable and scalable machine
learning technology for big data. This deep
learning framework gets a portable architecture
for extensible provided training on large scale
data. It writing code into a Java application
development.
Apache Mahout provides you the facility to define
your own calculating in a responsive way that
mostly explores on a big data platform then comes
entirely similar code into your app. Apache Singa
same as written code in Java.
TensorFlows custom architecture creates it
simply for users to build math top number of CPUs
with an also connect single API, It doesnt
matter to connect number of CPU with different
devices.
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Advantages of Machine learning

• As machine learning use different field such as
  retail, banking, medical and many other
  industries.
• Now many reputed brands are using machine
  learning to push relevant promotions.
• Machine learning in mostly used multiple data
  used in custom architecture
• It provides project deliver time reduce and
  better way utilize specific resources.
• It easily resolve complex process environments

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Machine learning Fact
It mainly goal to build machine learning
algorithm on statistical syllabus vector, matrix
and other basics. It is often more useful than
your chosen Java programming language. It
provide high quality library and framework widely
used in ML. It helps when developing huge
function method. Java and Python have better
benefits of exact output.
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