https://ai-blog.noorshomelab.dev/tags/distribution-strategies/Recent content in Distribution Strategies on AI VOIDHugoenSun, 26 Oct 2025 00:00:00 +0000https://ai-blog.noorshomelab.dev/tensorflow-guide/advanced-topics-distribution-strategies-tensorflow-lite/Sun, 26 Oct 2025 00:00:00 +0000https://ai-blog.noorshomelab.dev/tensorflow-guide/advanced-topics-distribution-strategies-tensorflow-lite/<h2 id="6-advanced-topics-and-best-practices">6. Advanced Topics and Best Practices</h2> <p>As you move beyond basic model building, two crucial aspects come into play for real-world applications: <strong>scaling your training</strong> to leverage powerful hardware and <strong>deploying your models</strong> to various environments, especially resource-constrained ones. This chapter covers TensorFlow&rsquo;s Distribution Strategies and TensorFlow Lite.</p> <h3 id="61-distribution-strategies-scaling-your-training">6.1 Distribution Strategies: Scaling Your Training</h3> <p>Training large models on massive datasets can be time-consuming. TensorFlow&rsquo;s <code>tf.distribute.Strategy</code> API allows you to easily distribute your training across multiple GPUs, multiple machines, or even Google&rsquo;s TPUs (Tensor Processing Units) with minimal changes to your code.</p>