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by Newman, Sam |
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by Bueno, Alex Soto, Eisele, Markus, Vinto, Natale |
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by Rahman, A N M Bazlur |
 | Think Distributed Systems (2025)
by Tornow, Dominik |
 | AI for Everyday IT: Accelerate workplace productivity (2025)
by LeMaire, Chrissy, Abshire, Brandon |
 | The AI Engineering Bible: The Complete and Up-to-Date Guide to Build, Develop and Scale Production Ready AI Systems (2025)
by Caldwell, Thomas R. |
 | Natural Language Processing in Action, Second Edition (2025)
by Lane, Hobson, Dyshel, Maria |
 | Machine Learning Algorithms in Depth (2025)
by Smolyakov, Vadim |
 | Ultimate Java for Data Analytics and Machine Learning: Unlock Java's Ecosystem for Data Analysis and Machine Learning Using WEKA, JavaML, JFreeChart, and Deeplearning4j (2025)
by Abhishek Kumar |
 | Artificial Intelligence Development with Java and Deeplearning4j: The Ultimate Guide to Building Scalable AI Systems with Cutting-Edge Techniques, Modern Frameworks, and Real-World Applications (2025)
by Hayes, Wilson |
 | AI Engineering: Building Applications with Foundation Models (2025)
by Huyen, Chip |
 | Designing Distributed Systems: Patterns and Paradigms for Scalable, Reliable Systems Using Kubernetes (2025)
by Burns, Brendan |
 | Artificial Intelligence with Java and Deeplearning4j: Master AI Development with Java’s Most Powerful Deep Learning Framework (2024)
by CARTER, THOMPSON |
 | Java Concurrency Patterns: Mastering Multithreading and Asynchronous Techniques (2024)
by Jones, Peter |
 | Mastering Java Concurrency: Threads, Synchronization, and Parallel Processing (2024)
by Jones, Peter |
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by Veen, Ron, Vlijmincx, David |
 | Java Concurrency and Parallelism: Master advanced Java techniques for cloud-based applications through concurrency and parallelism (2024)
by Wang, Jay |
 | Ultimate Java for Data Analytics and Machine Learning: Unlock Java's Ecosystem for Data Analysis and Machine Learning Using WEKA, JavaML, JFreeChart, and Deeplearning4j (English Edition) (2024)
by Kumar, Abhishek |
 | Architecting Data and Machine Learning Platforms: Enable Analytics and AI-Driven Innovation in the Cloud (2023)
by Tranquillin, Marco, Lakshmanan, Valliappa, Tekiner, Firat |
 | Patterns of Distributed Systems (Addison-Wesley Signature Series (Fowler)) (2023)
by Joshi, Unmesh |
 | Patterns of Distributed Systems (Addison-Wesley Signature Series (Fowler)) (2023)
by Joshi, Unmesh |
 | Akka in Action, Second Edition (2023)
by Abraham, Francisco Lopez-Sancho |
| Akka in Action, Second Edition (2023)
by Abraham, Francisco Lopez-Sancho |
 | Machine Learning System Design Interview (2023)
by Aminian, Ali, Xu, Alex |
 | Distributed Systems (2023)
by van Steen, Maarten, Tanenbaum, Andrew S. |
 | Applied Machine Learning and AI for Engineers: Solve Business Problems That Can't Be Solved Algorithmically (2022)
by Prosise, Jeff |
 | Foundations of Scalable Systems: Designing Distributed Architectures (2022)
by Gorton, Ian |
 | Natural Language Processing with Transformers, Revised Edition (2022)
by Tunstall, Lewis, Werra, Leandro von, Wolf, Thomas |
 | Designing Machine Learning Systems: An Iterative Process for Production-Ready Applications (2022)
by Huyen, Chip |
 | Machine Learning Engineering in Action (2022)
by Wilson, Ben |
 | Understanding Distributed Systems, Second Edition: What every developer should know about large distributed applications (2022)
by Vitillo, Roberto |
 | Machine Learning Design Patterns: Solutions to Common Challenges in Data Preparation, Model Building, and MLOps (2020)
by Lakshmanan, Valliappa, Robinson, Sara, Munn, Michael |
 | AI and Machine Learning for Coders: A Programmer's Guide to Artificial Intelligence (2020)
by Moroney, Laurence |
 | Practical Natural Language Processing: A Comprehensive Guide to Building Real-World NLP Systems (2020)
by Vajjala, Sowmya, Majumder, Bodhisattwa, Gupta, Anuj, Surana, Harshit |
 | Java Deep Learning Cookbook: Train neural networks for classification, NLP, and reinforcement learning using Deeplearning4j (2019)
by Raj, Rahul |
 | Introduction to Natural Language Processing (Adaptive Computation and Machine Learning series) (2019)
by Eisenstein, Jacob |
 | Reactive Streams in Java: Concurrency with RxJava, Reactor, and Akka Streams (2018)
by Davis, Adam L. |
 | Machine Learning in Java: Helpful techniques to design, build, and deploy powerful machine learning applications in Java, 2nd Edition (2018)
by Bhatia, AshishSingh, Kaluza, Bostjan |
 | Scala Programming Projects: Build real world projects using popular Scala frameworks like Play, Akka, and Spark (2018)
by Valot, Mikael, Jorand, Nicolas |
 | Hands-On Artificial Intelligence with Java for Beginners: Build intelligent apps using machine learning and deep learning with Deeplearning4j (2018)
by Joshi, Nisheeth |
 | Java Deep Learning Projects: Implement 10 real-world deep learning applications using Deeplearning4j and open source APIs (2018)
by Karim, Md. Rezaul |
 | Designing Distributed Systems: Patterns and Paradigms for Scalable, Reliable Services (2018)
by Burns, Brendan |
 | Concurrent Application Development using Akka with Scala (2017)
by Maltiar, Meetu, Hazrati, Vikas |
 | Akka Cookbook: Recipes for concurrent, fast, and reactive applications (2017)
by Ortiz, Hector Veiga, Mishra, Piyush |
 | Akka Cookbook: Recipes for concurrent, fast, and reactive applications (2017)
by Ortiz, Hector Veiga, Mishra, Piyush |
 | Distributed Systems (2017)
by van Steen, Maarten, Tanenbaum, Andrew S. |
 | Applied Akka Patterns: A Hands-On Guide to Designing Distributed Applications (2017)
by Nash, Michael, Waldron, Wade |
 | Mastering Akka (2016)
by Baxter, Christian |
 | Akka in Action (2016)
by Roestenburg, Raymond, Bakker, Rob, Williams, Rob |
 | Big Data SMACK: A Guide to Apache Spark, Mesos, Akka, Cassandra, and Kafka (2016)
by Estrada, Raul, Ruiz, Isaac |
