Throughout the book, you will work with hands-on Python machine learning projects in Python and TensorFlow 2.x. You will learn how to use WIT, SHAP, LIME, CEM, and other key explainable AI tools. You will explore tools designed by IBM, Google, Microsoft, and other advanced AI research ...
Denis Rothman创作的计算机网络小说《Hands-On Explainable AI(XAI) with Python》,已更新章,最新章节:undefined。EffectivelytranslatingAIinsightstobusinessstakeholdersrequirescarefulplanning,design,andvisualizationchoices.Describingt…
本书内容的组织非常自然流畅,各种观点都有清晰的实例证明,建议读者看第一遍的时候,不要去管那些公式,以后需要时再去深入推敲。 《Deep Learning withPython》 第三本是《Deep Learning with Python》。作者是 Keras 框架的构建者 Francois Chollet。不过这本书还得过段时间才能出版。但透过 Manning 的 MEAP 系统可...
* [Real-World Natural Language Processing](manning.com/books/real-) - 关于如何使用 Python 创建实用的 NLP 应用程序的早期访问书籍。 * [Grokking Machine Learning](manning.com/books/grokk) - 介绍最有价值的机器学习技术的抢先体验书籍。 * [Succeeding with AI](manning.com/books/succe) - 介绍如何管...
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恶意文件是指由攻击者专门设计的,在未经所有者许可的情况下用来访问计算机、损害或破坏系统,对保密性、完整性或可用性进行攻击的文件,是当前互联网安全的主要威胁之一。目前,比较主流的恶意文件包括恶意脚本、漏洞利用、蠕虫、木马和间谍软件以及他们的组合或变体。
Natural Language Processing with Python 的作者是 Steven Bird、Ewan Klein 和 Edward Loper。本书基于自然语言工具包 NLTK 库,内容按照难易程度顺序编排,不要求读者有 Python 编程的经验。是自然语言处理领域的一本实用入门指南,适合 Common Lisp 初学者及对其感兴趣的相关人员。 4. 智能Web 算法 作者是 Haralambos...
Enterprises understand the critical need to have access to and leverage reputable open-source projects with proper maintenance, updates, transparency, reliable support, and a sense of control to form a secure foundation for implementing AI solutions. Python AI Toolkit for IBM® z/OS® is a ...
Interpretable Machine Learning With Python: Learn to Build Interpretable High-Performance Models With Hands-On Real-World Examples Responsible AI (Hall, P., Chowdhury, R., 2023) Governance Safety Drift Marcus, G., and Davis, E. (2019). Rebooting AI: Building artificial intelligence we can trust...
人工神经网络,支持向量机,遗传算法等等算法;当然还有各个领域需要的算法,比如要让机器人自己在位置环境导航和建图就需要研究SLAM;总之算法很多需要时间的积累。需要掌握至少一门编程语言,比如C语言,MATLAB之类。毕竟算法的实现还是要编程的;如果深入到硬件的话,一些电类基础课必不可少。