Author: Zen and the Art of Computer Programming
1 Introduction
PyTorch is a Python-based open source machine learning library that supports efficient execution of tensor operations. In this series of tutorials, we will lead you to explore the powerful functions of PyTorch step by step, master the basic knowledge of PyTorch for a series of functions such as deep learning model construction, training, and reasoning, and be able to easily write reusable Practical machine learning projects. In this tutorial, I will focus on how to use PyTorch to build a deep learning model, how to perform deep learning training, evaluation and deployment, and also compare and apply it with other deep learning frameworks TensorFlow and Keras. This tutorial is mainly suitable for people who have a certain understanding of PyTorch but want to learn more about some of its details and capabilities. I hope readers can continue to summarize and accumulate their own knowledge during the learning process. The content of this tutorial is as follows:
- Deep learning basics
- PyTorch installation configuration and basic usage methods
- PyTorch data loading and preprocessing
- PyTorch deep learning model construction
- PyTorch deep learning model training and optimization strategy
- PyTorch deep learning model verification and saving
- Comparison and practice of TensorFlow and Keras
- Model inference and deployment
- Data sets and actual cases are shared. I hope everyone can benefit from this tutorial.
2. Basic knowledge of deep learning
First, we need to understand some basic concepts and terminology about deep learning.2.1 What is deep learning
Deep learning (Deep Learning) is a branch of computer science. Its research purpose is to make machines, like the human brain, "understand" complex, multi-modal natural environments such as images, audio, and text, and generate information about them. Effective control feedback. The core of deep learning is a deep model composed of neural networks. The basic unit of this model is neurons. It accepts input information and passes through multiple hidden