Book Content
chapters • 8h36m total length
R is a popular programming language used by statisticians and mathematicians for statistical analysis, and is popularly used for deep learning. This book demonstrates end-to-end implementations of five real-world projects on popular topics in deep learning such as handwritten digit recognition, traffic light detection, fraud detection, text generation, and sentiment analysis. You'll see how to train effective neural networks in R—including convolutional neural networks, recurrent neural networks and LSTMs—and also see how neural networks can be trained using GPU capabilities. You will use popular R libraries and packages—such as MXNetR, H2O, deepnet, and more—to implement the projects. By the end of this book, you will have a better understanding of deep learning concepts and techniques and how to use them in a practical setting.
Offered by
chapters • 8h36m total length
Need training for your whole team? Get bulk pricing, LMS integration, and dedicated support.
Join thousands of companies that trust Calibr to power their learning and development initiatives.















Start training your team in minutes!