TensorFlow Tutorial: From Tensors to Training
Socratica
Learn the foundations of TensorFlow in Python, starting with tensors and working up to building and training neural networks with Keras.
We cover what tensors are, how shapes and data types work, how TensorFlow handles device placement on CPUs and GPUs, and how Keras helps you build models using the Sequential API, Functional API, and model subclassing. Then we walk through the basic training workflow: compiling a model, choosing an optimizer and loss function, training with batches and epochs, validating results, and using callbacks like early stopping and model checkpoints.
This is a practical introduction for Python programmers who want to understand how TensorFlow works without skipping the core ideas.
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We cover what tensors are, how shapes and data types work, how TensorFlow handles device placement on CPUs and GPUs, and how Keras helps you build models using the Sequential API, Functional API, and model subclassing. Then we walk through the basic training workflow: compiling a model, choosing an optimizer and loss function, training with batches and epochs, validating results, and using callbacks like early stopping and model checkpoints.
This is a practical introduction for Python programmers who want to understand how TensorFlow works without skipping the core ideas.
Python Merch from Socratica:
https://shop.socratica.com/collections/python-merch
Support Socratica on Patreon:
https://www.patreon.com/socratica
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