Description This book is an exploration of Deep Learning in Python using Py Torch.
This book will help you to understand: - Why Py Torch for Deep Learning? - Getting Started with Py Torch - Building a Neural Network - Loading and Processing Data - Convolutional Neural Networks - Transfer Learning - Developing Distributed Applications - Word Embeddings - Moving a Model from Py Torch to Caffe2 - Custom C Extensions - Neural Transfer with Py Torch Tags: pytorch Deep learning, python programming, python, python data science handbook, neural network python, tensorflow python, tensorflow for Deep learning, python code programming..
You will also know how to use the inbuilt data for training your neural network models.
The process of loading your own data into Py Torch for training neural network models has also been discussed.
Examples of such data include images and text.
You are guided on how to train such models with data of various types.
The author helps you understand how to create neural network models with Tensor Flow.
Deep Learning in Python with Py Torch simply involves the creation of neural network models.
The author helps you know how build neural network graphs in Py Torch.
Py Torch works using the concept of graphs.
This involves installing Py Torch and writing your first code.
You will know the initial steps of getting started with Py Torch in Python.
The author guides you on how to create neural network models using Py Torch in Python.
Description This book is an exploration of Deep Learning in Python using Py Torch
