Deep Learning with PyTorch

Deep Learning with PyTorch pdf epub mobi txt 电子书 下载 2025

Eli Stevens has worked in Silicon Valley for the past 15 years as a software engineer, and the past 7 years as Chief Technical Officer of a startup making medical device software.

Luca Antiga is co-founder and CEO of an AI engineering company located in Bergamo, Italy, and a regular contributor to PyTorch.

出版者:Manning Publications
作者:Eli Stevens
出品人:
页数:450
译者:
出版时间:2020-6-9
价格:USD 49.99
装帧:Paperback
isbn号码:9781617295263
丛书系列:
图书标签:
  • 机器学习 
  • 深度学习 
  • PyTorch 
  • 计算机科学 
  • deep-learning 
  • 2020 
  • 人工智能 
  • 计算机 
  •  
想要找书就要到 图书目录大全
立刻按 ctrl+D收藏本页
你会得到大惊喜!!

Deep Learning with PyTorch teaches you how to implement deep learning algorithms with Python and PyTorch. This book takes you into a fascinating case study: building an algorithm capable of detecting malignant lung tumors using CT scans. As the authors guide you through this real example, you'll discover just how effective and fun PyTorch can be. After a quick introduction to the deep learning landscape, you'll explore the use of pre-trained networks and start sharpening your skills on working with tensors. You'll find out how to represent the most common types of data with tensors and how to build and train neural networks from scratch on practical examples, focusing on images and sequences.

After covering the basics, the book will take you on a journey through larger projects. The centerpiece of the book is a neural network designed for cancer detection. You'll discover ways for training networks with limited inputs and start processing data to get some results. You'll sift through the unreliable initial results and focus on how to diagnose and fix the problems in your neural network. Finally, you'll look at ways to improve your results by training with augmented data, make improvements to the model architecture, and perform other fine tuning.

what's inside

Using the PyTorch tensor API

Understanding automatic differentiation in PyTorch

Training deep neural networks

Monitoring training and visualizing results

Implementing modules and loss functions

Loading data in Python for PyTorch

Interoperability with NumPy

Deploying a PyTorch model for inference

具体描述

读后感

评分

评分

评分

评分

评分

用户评价

评分

感觉还好 等出版了再看吧

评分

感觉还好 等出版了再看吧

评分

书不错,由浅入深的介绍了PyTorch,书里面有很多的例子可以学习。

评分

书是不难懂,但懂了也还是感觉啥也不会(大概可以入一下门吧

评分

好像好多地方也不是讲得很清晰,起基本的扫盲作用,多写代码吧

本站所有内容均为互联网搜索引擎提供的公开搜索信息,本站不存储任何数据与内容,任何内容与数据均与本站无关,如有需要请联系相关搜索引擎包括但不限于百度google,bing,sogou

© 2025 book.wenda123.org All Rights Reserved. 图书目录大全 版权所有