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Machine Learning in Java - Helpful techniques to design, build, and deploy powerful machine learning applications in Java, 2nd Edition (Paperback, 2nd Revised edition)
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Machine Learning in Java - Helpful techniques to design, build, and deploy powerful machine learning applications in Java, 2nd Edition (Paperback, 2nd Revised edition)
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Leverage the power of Java and its associated machine learning
libraries to build powerful predictive models Key Features Solve
predictive modeling problems using the most popular machine
learning Java libraries Explore data processing, machine learning,
and NLP concepts using JavaML, WEKA, MALLET libraries Practical
examples, tips, and tricks to help you understand applied machine
learning in Java Book DescriptionAs the amount of data in the world
continues to grow at an almost incomprehensible rate, being able to
understand and process data is becoming a key differentiator for
competitive organizations. Machine learning applications are
everywhere, from self-driving cars, spam detection, document
search, and trading strategies, to speech recognition. This makes
machine learning well-suited to the present-day era of big data and
Data Science. The main challenge is how to transform data into
actionable knowledge. Machine Learning in Java will provide you
with the techniques and tools you need. You will start by learning
how to apply machine learning methods to a variety of common tasks
including classification, prediction, forecasting, market basket
analysis, and clustering. The code in this book works for JDK 8 and
above, the code is tested on JDK 11. Moving on, you will discover
how to detect anomalies and fraud, and ways to perform activity
recognition, image recognition, and text analysis. By the end of
the book, you will have explored related web resources and
technologies that will help you take your learning to the next
level. By applying the most effective machine learning methods to
real-world problems, you will gain hands-on experience that will
transform the way you think about data. What you will learn
Discover key Java machine learning libraries Implement concepts
such as classification, regression, and clustering Develop a
customer retention strategy by predicting likely churn candidates
Build a scalable recommendation engine with Apache Mahout Apply
machine learning to fraud, anomaly, and outlier detection
Experiment with deep learning concepts and algorithms Write your
own activity recognition model for eHealth applications Who this
book is forIf you want to learn how to use Java's machine learning
libraries to gain insight from your data, this book is for you. It
will get you up and running quickly and provide you with the skills
you need to successfully create, customize, and deploy machine
learning applications with ease. You should be familiar with Java
programming and some basic data mining concepts to make the most of
this book, but no prior experience with machine learning is
required.
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