TensorFlow for Computer Vision – Full Tutorial for Beginners

Course Contents

(0:00:00) Introduction and where you can find me to ask questions
(0:01:21) Course outline
(0:05:11) Who’s this course for
(0:05:35) Why learn TensorFlow
(0:06:25) We will be using an IDE and not notebooks
(0:07:25) Visual Studio Code (how to download and install it)
(0:10:50) Miniconda – how to install it
(0:13:23) Miniconda – why we need it
(0:17:24) How are we going to use conda virtual environments in VS Code?
(0:21:20) Installing Tensorflow 2 (CPU version)
(0:29:56) Installing Tensorflow 2 (GPU version)
(0:43:34) What do we want to achieve?
(0:45:26) Exploring MNIST dataset
(1:05:54) Tensorflow layers
(1:09:44) Building a neural network the sequential way
(1:27:22) Compiling the model and fitting the data
(2:00:52) Building a neural network the functional way
(2:08:33) Building a neural network the Model Class way
(2:14:31) Things we should add
(2:18:29) Restructuring our code for better readability
(2:23:11) First part summary
(2:24:12) What we want to achieve
(2:25:23) Downloading and exploring the dataset
(2:34:20) Preparing train and validation sets
(2:53:37) Preparing the test set
(3:10:17) Building a neural network the functional way
(3:22:12) Creating data generators
(3:31:39) Instantiating the generators
(3:35:37) Compiling the model and fitting the data
(3:40:34) Adding callbacks
(3:52:08) Evaluating the model
(3:58:04) Potential improvements
(4:08:49) Running prediction on single images
(4:23:05) Second part summary
(4:23:56) Where you can find me if you have questions