TensorFlow Study Guide 2026

Everything you need to pass the TensorFlow exam in one place: the exam format, every topic to study, real practice questions with explanations, flashcards, and full-length practice tests. Free, no sign-up needed.

📚 TensorFlow Topics to Study (22)

✍️ Sample TensorFlow Questions & Answers

1. What is broadcasting in TensorFlow?
Automatic expansion of smaller tensors to match larger tensor shapes

Broadcasting allows TensorFlow to perform operations on tensors with different shapes by automatically expanding dimensions.

2. Which function creates a tf.data.Dataset from a list of NumPy arrays?
tf.data.Dataset.from_tensor_slices()

from_tensor_slices() slices the first dimension of each array to create individual dataset elements.

3. What is dynamic range quantization in TFLite?
Quantizes weights to int8 at conversion time but keeps activations as float at runtime

Dynamic range quantization reduces weight size by ~4x by storing them as int8, while activations are quantized dynamically during inference.

4. What does the tf.function decorator do in TensorFlow 2?
Compiles a Python function into a TensorFlow graph for faster execution

tf.function traces the Python function and compiles it into a static computation graph, enabling performance optimizations like XLA.

5. Which method creates a dataset from a list of filenames?
tf.data.Dataset.list_files()

tf.data.Dataset.list_files() creates a dataset of file path strings matching a glob pattern.

6. Which tf.data method applies a function to each element of a dataset?
dataset.map()

dataset.map() applies a given function to every element in the dataset, enabling preprocessing transformations.

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TensorFlow Study Guide 2026 — Exam Format, Topics & Practice Questions