Language:
English
Pages:
1 online resource (1 video file, approximately 3 hr., 52 min.)
Edition:
1st edition
Keywords:
Internet videos
;
Streaming video
;
Electronic videos ; local
;
Vidéos sur Internet
;
Vidéo en continu
;
streaming video
;
Internet videos
;
Streaming video
;
Electronic videos
Abstract:
Wow! A brand new set of techniques to study and apply. The videos are great, amazingly organized, and go step by step to introduce such a complex topic. Arnaldo Ayala, Software Architect, Consultores Informáticos The Keras package for R brings the power of deep learning to R users. Deep Learning with R in Motion locks in the essentials of deep learning and teaches you the techniques you'll need to start building and using your own neural networks for text and image processing. Instructor Rick Scavetta takes you through a hands-on ride through the powerful Keras package, a TensorFlow API. You'll start by digging into case studies for how and where to use deep learning. Then, you'll master the essential components of a deep learning neural network as you work hands-on through your first examples. You'll continue by exploring dense and recurrent neural networks, convolutional and generative networks, and how they all work together. And that's just the beginning! You'll go steadily deeper, making your network more robust and efficient. As your work through each module, you'll train your network and pick up the best practices used by experts like expert instructor Rick Scavetta, Keras library creator and author of Deep Learning in Python François Chollet , and JJ Allaire , founder of RStudio, creator of the R bindings for Keras, and coauthor of Deep Learning in R ! You'll beef up your skills as you practice with R-based applications in computer vision, natural-language processing, and generative models, ready for the real-world. Machine learning has made remarkable progress in recent years. Deep learning systems have revolutionized image recognition, natural-language processing, and other applications for identifying complex patterns in data. The Keras library provides data scientists and developers working in R a state-of-the-art toolset for tackling deep learning tasks! Inside: The 4 steps of Deep Learning Using R with Keras and TensorFlow Working with the Universal Workflow Computer vision with R Recurrent neural networks Everyday best practices Generative deep learning You'll need intermediate R programming skills. No previous experience with machine learning or deep learning is assumed. Rick Scavetta is a biologist, workshop trainer, freelance data scientist, cofounder of Science Craft, and founder of Scavetta Academy, companies dedicated to helping scientists better understand and visualize their data. Rick's practical, hands-on exposur...
Note:
Online resource; Title from title screen (viewed August 28, 2019)
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