TensorFlow-Tutorials

Why we included this project

This is one of the friendliest self-paced paths into deep learning we have come across. Each notebook covers a single topic with heavily commented code, so a beginner can work through convolutional networks, fine-tuning, reinforcement learning, and hyper-parameter optimization without drowning in jargon. Nearly every tutorial has a matching YouTube walkthrough, which helps if you prefer hearing someone explain the theory before running the code yourself. Several notebooks have been updated for TensorFlow 2 and can run directly in Google Colab, so there is no local setup to fight with. Treat it as a structured way to build your fundamentals rather than a library you would drop into a production stack.