A highly accessible, step-by-step introduction to deep learning, written in an engaging, question-and-answer style.
The Little Learner introduces deep learning from the bottom up, inviting students to learn by doing. With the characteristic humor and Socratic approach of classroom favorites The Little Schemer and The Little Typer, this kindred text explains the workings of deep neural networks by constructing them incrementally from first principles using little programs that build on one another. Starting from scratch, the reader is led through a complete implementation of a substantial application: a recognizer for noisy Morse code signals. Example-driven and highly accessible, The Little Learner covers all of the concepts necessary to develop an intuitive understanding of the workings of deep neural networks, including tensors, extended operators, gradient descent algorithms, artificial neurons, dense networks, convolutional networks, residual networks, and automatic differentiation.
Conversational style, illustrations, and question-and-answer format make deep learning accessible and fun
Incremental approach constructs advanced concepts from first principles
Presents key ideas of machine learning using a small, manageable subset of the Scheme language
Suitable for anyone with knowledge of high school math and some programming experience

本书是经典的计算机网络教材，采用作者独创的自顶向下方法来讲授计算机网络的原理及其协议，自第1版出版以来已经被数百所大学和学院选作教材，被译为14种语言。
第7版保持了以前版本的特色，继续关注因特网和计算机网络的现代处理方式，注重原理和实践，为计算机网络教学提供一种新颖和与时俱进的方法。同时，第7版进行了相当多的修订和更新，首次改变了各章的组织结构，将网络层分成两章（第4章关注网络层的数据平面，第5章关注网络层的控制平面），并将网络管理主题放入新的第5章中。此外，为了反映自第6版以来计算机网络领域的新变化，对其他章节也进行了更新，删除了FTP和分布式散列表的材料，用流行的因特网显式拥塞通告（ECN）材料代替了ATM网络的材料，更新了有关802.11（即WiFi）网络和蜂窝网络（包括4G和LTE）的材料，全面修订并增加了新的课后习题，等等。
本书适合作为计算机、电气工程等专业本科生的“计算机网络”课程教科书，同时也适合网络技术人员、专业研究人员阅读。