The Advanced Guide to Deep Learning and Artificial Intelligence Bundle - BuzzTechy

This High-Intensity 14.5 Hour Bundle Will Help You Help Computers Address Some of Humanity's Biggest Problems In this course, intended to expand upon your knowledge of neural networks and deep learning, you'll harness these concepts for computer vision using convolutional neural networks. Going in-depth on the concept of convolution, you'll discover its wide range of applications, from generating image effects to modeling artificial organs. In this course, you'll dig deep into deep learning, discussing principal components analysis and a popular nonlinear dimensionality reduction technique known as t-distributed stochastic neighbor embedding (t-SNE). From there you'll learn about a special type of unsupervised neural network called the autoencoder, understanding how to link many together to get a better performance out of deep neural networks. A recurrent neural network is a class of artificial neural network where connections form a directed cycle, using their internal memory to process arbitrary sequences of inputs.