Hands-On Deep Learning with Go
The Go ecosystem comprises some really powerful Deep Learning tools. This book shows you how to use these tools to train and deploy scalable Deep Learning models. You will explore a number of modern Neural Network architectures such as CNNs, RNNs, and more. By the end, you will be able to train your own Deep Learning models from scratch, using the power of Go.
Offered by
Difficulty Level
Intermediate
Completion Time
8h4m
Language
English
About Book
Who Is This Book For?
This book is for data scientists, machine learning engineers, and AI developers who want to build state-of-the-art deep learning models using Go. Familiarity with basic machine learning concepts and Go programming is required to get the best out of this book.
Hands-On Deep Learning with Go
- About Book
- Who Is This Book For?
- Book Content
Book content
chapters • 8h4m total length
Introduction to Deep Learning in Go
What Is a Neural Network and How Do I Train One?
Beyond Basic Neural Networks - Autoencoders and RBMs
CUDA - GPU-Accelerated Training
Next Word Prediction with Recurrent Neural Networks
Object Recognition with Convolutional Neural Networks
Maze Solving with Deep Q-Networks
Generative Models with Variational Autoencoders
Building a Deep Learning Pipeline
Scaling Deployment
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