Deep Learning with R for Beginners: Design neural network models in R 3.5 using TensorFlow, Keras, and MXNet

Price: $27.99
(as of Dec 25,2024 14:59:36 UTC – Details)

ASIN ‏ : ‎ B07S58W15J
Publisher ‏ : ‎ Packt Publishing; 1st edition (May 20, 2019)
Publication date ‏ : ‎ May 20, 2019
Language ‏ : ‎ English
File size ‏ : ‎ 29595 KB
Text-to-Speech ‏ : ‎ Enabled
Screen Reader ‏ : ‎ Supported
Enhanced typesetting ‏ : ‎ Enabled
X-Ray ‏ : ‎ Not Enabled
Word Wise ‏ : ‎ Not Enabled
Print length ‏ : ‎ 614 pages

Are you interested in diving into the world of deep learning with R? Look no further! In this post, we will explore how to design neural network models in R 3.5 using popular deep learning libraries such as TensorFlow, Keras, and MXNet.

Deep learning has revolutionized the field of artificial intelligence, allowing for the development of powerful models that can learn complex patterns from data. With R, a popular programming language among data scientists, you can harness the power of deep learning to tackle a wide range of problems, from image recognition to natural language processing.

In this post, we will walk you through the process of building neural network models in R using TensorFlow, Keras, and MXNet. We will cover the basics of deep learning, including how neural networks work and how to train them using gradient descent. We will also provide hands-on examples to help you get started with building your own deep learning models in R.

Whether you are a beginner looking to get started with deep learning or an experienced data scientist looking to expand your skillset, this post is for you. So grab your computer, fire up R, and let’s dive into the exciting world of deep learning with R!
#Deep #Learning #Beginners #Design #neural #network #models #TensorFlow #Keras #MXNet