Master intricacies of R deep learning packages such as mxnet & tensorflow
Learn application on deep learning in different domains using practical examples from text, image and speech
Guide to set-up deep learning models using CPU and GPU
Description
Deep Learning is the next big thing. It is a part of machine learning. It's favorable results in applications with huge and complex data is remarkable. Simultaneously, R programming language is very popular amongst the data miners and statisticians.
This book will help you to get through the problems that you face during the execution of different tasks and Understand hacks in deep learning, neural networks, and advanced machine learning techniques. It will also take you through complex deep learning algorithms and various deep learning packages and libraries in R. It will be starting with different packages in Deep Learning to neural networks and structures. You will also encounter the applications in text mining and processing along with a comparison between CPU and GPU performance.
By the end of the book, you will have a logical understanding of Deep learning and different deep learning packages to have the most appropriate solutions for your problems.
Who is this book for?
Data science professionals or analysts who have performed machine learning tasks and now want to explore deep learning and want a quick reference that could address the pain points while implementing deep learning. Those who wish to have an edge over other deep learning professionals will find this book quite useful.
What you will learn
Build deep learning models in different application areas using TensorFlow, H2O, and MXnet.
Analyzing a Deep boltzmann machine
Setting up and Analysing Deep belief networks
Building supervised model using various machine learning algorithms
Set up variants of basic convolution function
Represent data using Autoencoders.
Explore generative models available in Deep Learning.
Discover sequence modeling using Recurrent nets
Learn fundamentals of Reinforcement Leaning
Learn the steps involved in applying Deep Learning in text mining
Explore application of deep learning in signal processing
Utilize Transfer learning for utilizing pre-trained model
Please wait for the author to complete the book. The way the book is structured it is a well thought out template for a cookbook. The book has the skeletal structure and, imagine, the authors are working on it to complete it soon. Can not wait for the book.
Achyutuni Sri Krishna Rao 是数据科学家、土木工程师和作家,目前在 ZS 咨询公司担任数据科学顾问。他获得了新加坡国立大学企业商业分析和机器学习的硕士学位、印度 Warangal 国家技术研究所的学士学位。Sri Krishna 在土木工程研究领域发表了多篇文章,并参与了 Packt 出版的名为 Algorithms and Data Structures Using R 一书的写作。
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