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Introduction
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What we want to achieve
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Why Java
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Java can be nice
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Java is not cool
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When is this a bad idea
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When can it make sense
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Why
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TensorFlow Basics
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TensorFlow Architecture
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What is TensorFlow
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Operations
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Sessions
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How TensorFlow training works
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How does learning work
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Plan of attack
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Defining the initial graph
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Running the session
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amnesty
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mirror
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initial code
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debugging
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running the graph
Description:
Explore TensorFlow training on the Java Virtual Machine in this 34-minute conference talk by Christoph Henkelmann from DIVISIO at MLCon. Learn why and when combining TensorFlow models with Java can be beneficial for commercial projects running on the JVM. Discover TensorFlow basics, including its architecture, operations, and sessions. Understand how TensorFlow training works and follow the step-by-step process of defining an initial graph, running sessions, and debugging. Gain insights into the advantages and challenges of using Java for machine learning tasks, and see practical examples of implementing TensorFlow in a JVM environment.

TensorFlow Training on the JVM

MLCon | Machine Learning Conference
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