TensorFlow can do some amazing things when it comes to computer vision.

We just published a full course on the freeCodeCamp.org YouTube channel that will teach you how to use TensorFlow 2 for computer vision applications.

Nour Islam Mokhtari created this course. Nour is a Machine Learning Engineer and experienced teacher.

The course shows you how to create two computer vision projects. The first involves an image classification model with a prepared dataset. The second is a more real-world problem where you will have to clean and prepare a dataset before using it.

MNIST Dataset with labels

Here are the topics covered in this course:

  • Why learn Tensorflow
  • We will be using an IDE and not notebooks
  • Visual Studio Code (how to download and install it)
  • Miniconda - how to install it
  • Miniconda - why we need it
  • How are we going to use conda virtual environments in VS Code?
  • Installing Tensorflow 2 (CPU version)
  • Installing Tensorflow 2 (GPU version)
  • What do we want to achieve?
  • Exploring MNIST dataset
  • Tensorflow layers
  • Building a neural network the sequential way
  • Compiling the model and fitting the data
  • Building a neural network the functional way
  • Building a neural network the Model Class way
  • Things we should add
  • Restructuring our code for better readability
  • First part summary
  • What we want to achieve
  • Downloading and exploring the dataset
  • Preparing train and validation sets
  • Preparing the test set
  • Building a neural network the functional way
  • Creating data generators
  • Instantiating the generators
  • Compiling the model and fitting the data
  • Adding callbacks
  • Evaluating the model
  • Potential improvements
  • Running prediction on single images

Watch the full course below or on the freeCodeCamp.org YouTube channel (4.5-hour watch).