Deep learning enables efficient and accurate learning from data. Developers working with R will be able to put their knowledge to work with this practical guide to deep learning. The book provides a hands-on approach to implementation and associated methodologies that will have you up-and-running, and productive in no time. This book covers the following exciting features:
- Explore and implement deep learning to solve various real-world problems using modern R libraries such as TensorFlow, MXNet, H20, and Deepnet
- Design a feedforward neural network to see how the activation function computes an output
- Create an image recognition model using convolutional neural networks (CNNs)
- Prepare data, decide hidden layers and neurons and train your model with the backpropagation algorithm
- Apply text cleaning techniques to remove uninformative text using NLP
- Build, train, and evaluate a GAN model for face generation
- Understand the concept and implementation of reinforcement learning in R
It’s hard to believe it’s already been two years since Data Science for Fundraising was launched. During this time, Ashutosh Nandeshwar and I have connected with other lifelong learners and practitioners who are now applying data science to solve problems, as well as identify new opportunities, within their respective communities, organizations, and institutions.
- Click here to learn more about the book and how to apply data science across the donor lifecycle.
- Click here to get a Kindle or paperback copy on Amazon!
- Click here to access a free, online version of the book!
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Best wishes on your data science journey!