The Machine Vision course focuses on image recognition using neural networks in Python. During the course we will look at the basics of neural networks: neuron, layers, connections, backpropagation of errors and multilayer perceptron. Let’s study the features of training and optimization of neural networks.

Let’s dive into convolutional neural networks and look at the LeNet, AlexNet, VGG and ResNet architectures.

Let’s apply theoretical knowledge in practice. We use Python and Keras to create and train neural network models for successful recognition of handwritten digits – the MNIST set.

Let’s look at all the practical features of working with neural networks in Keras.

We will also use a training set of images of license plate numbers to recognize a real car license plate number.