About this nonfiction
R DEEP LEARNING PROJECTS : master the techniques to train and deploy neural networks in r by Liu, Yuxi (Hayden), Maldonado, Pablo is a nonfiction available to read on EtoBox.
5 real-world projects to help you master deep learning conceptsKey FeaturesMaster the different deep learning paradigms and build real-world projects related to text generation, sentiment analysis, fraud detection, and moreGet to grips with R's impressive range of Deep Learning libraries and frameworks such as deepnet, MXNetR, Tensorflow, H2O, Keras, and text2vecPractical projects that show you how to implement different neural networks with helpful tips, tricks, and best practicesBook DescriptionR is a popular programming language used by statisticians and mathematicians for statistical analysis, and is popularly used for deep learning. Deep Learning, as we all know, is one of the trending topics today, and is finding practical applications in a lot of domains. 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 learn how to train effective neural networks in R—including convolutional neural networks, recurrent neural networks, and LSTMs—and apply them in practical scenarios. The book also high
It is typically read by self-directed learners exploring a subject in depth.
Common subject areas: history, science, philosophy, social sciences.
- Author
- Liu, Yuxi (Hayden), Maldonado, Pablo
- Publisher
- PACKT PUBLISHING LIMITED
- Published
- 2018
- Language
- EN
- ISBN
- 9781788474559
- Category
- nonfiction
- Subjects
- Science, Mathematics, Computer Science