Dive into Deep Learning
简介：
这是一本开源的交互式书籍，以独特的形式提供，集成了文本，数学和代码，现在支持TensorFlow，PyTorch和Apache MXNet编程框架，完全通过Jupyter笔记本起草。这本书旨在教给人们机器学习中使用的不同算法。这本书的一大资产是它提供了所有的编码信息。在过去的几年里，一个由亚马逊科学家组成的团队一直在开发一本书，该书在被蓬勃发展的深度学习领域吸引的学生和开发人员中越来越受欢迎，深度学习是机器学习的一个子集，专注于大规模人工神经网络。这本书以独特的形式实现，集成了文本，数学和可运行的代码。本书完全通过Jupyter笔记本起草，是一个完全开源的生活文档，每次更新都会触发PDF，HTML和笔记本版本的更新。最近，作者在他们的书中添加了两个编程框架: PyTorch和TensorFlow。这本书最初是为MXNet编写的，在学生、开发人员和科学家的开源机器学习社区中具有更广泛的吸引力。它将教您如何在Kaggle，Google Colab和Amazon SageMaker中运行Jupyter笔记本。
英文简介：
This is an open source, interactive book provided in a unique form factor that integrates text, mathematics and code, now supports the TensorFlow, PyTorch, and Apache MXNet programming frameworks, drafted entirely through Jupyter notebooks.
The book is designed to teach people different algorithms used in machine learning. A big asset of the book is the fact it provides all the coding information.
Over the past few years, a team of Amazon scientists has been developing a book that is gaining popularity with students and developers attracted to the booming field of deep learning, a subset of machine learning focused on large-scale artificial neural networks.
The book arrives in a unique form factor, integrating text, mathematics, and runnable code. Drafted entirely through Jupyter notebooks, the book is a fully open source living document, with each update triggering updates to the PDF, HTML, and notebook versions.
Recently the authors added two programming frameworks to their book: PyTorch and TensorFlow. That gives the book - originally written for MXNet - even broader appeal within the open-source machine-learning community of students, developers, and scientists.
It will teaches you how to run Jupyter notebooks in Kaggle, Google Colab, and Amazon SageMaker.
- 书名
- Dive into Deep Learning
- 译名
- 深入学习深度学习
- 语言
- 英语
- 页数
- 1151页
- 大小
- 42.62 MB
- 标签
- 深度学习
- 机器学习
- 下载
Dive into Deep Learning.pdf- 密码
- 65536
最后更新：2025-04-12 23:58:07