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TensorFlow Training on the JVM | Christoph Henkelmann
Explore the viability of TensorFlow training on the JVM, its compatibility with Java and Kotlin, and the benefits and drawbacks of this option for deep learning.
- TensorFlow Training on JVM is a viable option for deep learning on Java.
- Maarten, Google’s JVM-based tensorflow API won’t be deprecated or removed.
- In Maarten, the JVM-based tensorflow API is designed to communicate with the tensor API in Java.
- Using Java and Kotlin for deep learning is a good choice for commercial applications.
- TensorFlow is not smarter or faster just because it is Google.
- The tf data pipeline doesn’t do anything essentially different from pre-processing in Java.
- The tensorflow persistence RP is really ugly and not easy to use.
- Java is fast and can be used for deep learning.
- The JVM-based tensorflow API is a good choice for those who want to use tensorflow with Java.
- The tensorflow API is not stable and can change often.
- The tensorflow graph is a file extension.
- The use of Kotlin for deep learning is recommended.
- TensorFlow is not a beginner’s tool for machine learning.