Key Features
- This comprehensive book shows you exactly how you can take your Java data science applications to production seamlessly
- Dive deep into analytics, supervised and unsupervised learning, and much more with ease
- Explore Java’s various libraries to efficiently build and deploy data applications for the enterprise
Book Description
Java is the language of choice if you want to bring data science to production, thanks to its stability and rich set of libraries. Major big data solutions including Hadoop are written in Java. This book will teach you how to perform data analysis on big data in a much more sophisticated manner. If you are willing to take your data products to enterprise without changing your stack, this book will tell you how to do it with ease.
This book will quickly brush up on what you already know about using Java in data science applications and will then dive quickly into the advanced concepts to implement data science in production. The book covers topics such as advanced data science algorithms, preparing tricky data, advanced clustering, regression, classification, prediction, machine learning, and more.
We’ll teach you how data science can be used effectively to analyze unstructured data and big data. This book will enable you to tackle the problems of advanced visualization, advanced statistics, scaling data science applications, deploying these applications in production, and many more. You will also learn about natural language processing, real-time analytics, deep learning, and neural networks.
What you will learn
- Get a solid understanding of the data processing toolbox available in Java
- Explore the data science ecosystem available in Java and other JVM languages
- Understand when to use Java and what is best to do outside of Java
- Deal with the machine learning task at hand and bring the results directly to production
- Get state-of-the-art performance with xgboost and deeplearning4j
- Build applications that scale and process large amounts of data in real time
About the Author
Alexey Grigorev is a skilled Data Scientist and Software Engineer with more than five years of professional experience. Now he works as a Data Scientist at Searchmetrics Inc. In his day-to-day job, he actively uses R and Python for data cleaning, data analysis, and modeling. He is a reviewer of other Packt Publishing books on data analysis such as Test-Driven Machine Learning and Mastering Data Analysis with R
You can find him LinkedIn at https://de.linkedin.com/in/agrigorev.
