How TensorFlow Really Works: Tensors, Shapes & Real Business Examples

TensorFlow isn’t only “neural networks” — at the beginning, it’s a powerful tensor math engine. In this video, you’ll learn what TensorFlow is, what a Tensor is, and the key concepts that make everything work: rank, shape, dtype, indexing/slicing, reshaping, broadcasting, and aggregation (reduce operations).

Then we make it practical with hands-on e-commerce scenarios using only core TensorFlow ops (no Keras, no layers). You’ll calculate daily revenue, checkout totals (discount + VAT), flag suspicious orders, find best-selling products, analyze trends using slicing, compute shipping tiers with `tf.where`, and normalize data with z-scores — all step by step in a Jupyter notebook.

If you’re new to TensorFlow, this is the clean foundation you need before moving into gradients, training, and models.

Code notebook used in the video: [GitHub link here]