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Scala Machine Learning Projects. Build real-world machine learning and deep learning projects with Scala

(ebook) (audiobook) (audiobook) Książka w języku angielskim
Scala Machine Learning Projects. Build real-world machine learning and deep learning projects with Scala Md. Rezaul Karim - okladka książki

Scala Machine Learning Projects. Build real-world machine learning and deep learning projects with Scala Md. Rezaul Karim - okladka książki

Scala Machine Learning Projects. Build real-world machine learning and deep learning projects with Scala Md. Rezaul Karim - audiobook MP3

Scala Machine Learning Projects. Build real-world machine learning and deep learning projects with Scala Md. Rezaul Karim - audiobook CD

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470
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Machine learning has had a huge impact on academia and industry by turning data into actionable information. Scala has seen a steady rise in adoption over the past few years, especially in the fields of data science and analytics. This book is for data scientists, data engineers, and deep learning enthusiasts who have a background in complex numerical computing and want to know more hands-on machine learning application development.
If you're well versed in machine learning concepts and want to expand your knowledge by delving into the practical implementation of these concepts using the power of Scala, then this book is what you need! Through 11 end-to-end projects, you will be acquainted with popular machine learning libraries such as Spark ML, H2O, DeepLearning4j, and MXNet.
At the end, you will be able to use numerical computing and functional programming to carry out complex numerical tasks to develop, build, and deploy research or commercial projects in a production-ready environment.

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O autorze książki

Md. Rezaul Karim is a researcher, author, and data science enthusiast with a strong computer science background, coupled with 10 years of research and development experience in machine learning, deep learning, and data mining algorithms to solve emerging bioinformatics research problems by making them explainable. He is passionate about applied machine learning, knowledge graphs, and explainable artificial intelligence (XAI).
Currently, he is working as a research scientist at Fraunhofer FIT, Germany. He is also a PhD candidate at RWTH Aachen University, Germany. Before joining FIT, he worked as a researcher at the Insight Centre for Data Analytics, Ireland. Previously, he worked as a lead software engineer at Samsung Electronics, Korea.

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