Deep Learning with Tensorflow

This course show me the principles of neural networks using basic concepts of Tensorflow, unsupervised and supervised deep learning methods using TensorFlow, the archiqueture and execution pipeline of this methods and how to apply them to solve real problems. Likewise it also teach me how use TensorFlow in curve fitting, regression, classification and minimization of error functions, to tune the weights and biases of a Neural Networks while being trained using backpropagation.

The methods learned where:

• Supervised: Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and Long Short-Term Memory Model (LSTM).
• Unsupervised: Restricted Boltzmann Machines (RBMs) and Autoencoders