Hands-On Mathematics for Deep Learning: Build a solid mathematical foundation for training efficient deep neural networks
Author:Jay Dawani (Author)
Publisher finelybook 出版社: Packt Publishing
Edition 版本:N/A
Publication Date 出版日期:2020-06-12
Language 语言:English
Print Length 页数:364pages
ISBN-10:1838647295
ISBN-13:978-1838647292
Book Description
About the Author
Jay Dawani is a former professional swimmer turned mathematician and computer scientist. At present, he is the founder of Lemurian Labs – a startup that is developing a next generation AI accelerator to enable deep learning on edge devices, as well as a platform for developing enterprise scale autonomous robotics. Previously he was the Director of Artificial Intelligence at Geometric Energy Corporation where he led research efforts and developed various AI based solutions for industry. He has also advised many companies including Spacebit Technology on the development of their Lunar Rover, and SiaClassic Foundation on the development of their decentralized information storage and retrieval platform. He has spent the last three years researching at the frontiers of AI with a focus on computer vision, reinforcement learning, open-ended learning, deep learning, multi-agent and complex systems, and artificial general intelligence.
下载地址
PDF, EPUB | 285 MB | 2020-07-03
未经允许不得转载:finelybook » Hands-On Mathematics for Deep Learning: Build a solid mathematical foundation for training efficient deep neural networks
相关推荐
ChatGPT: Principles and Architecture
Digital Transformation Best Practices: Empower your business with data-driven strategies and Agile technologies
Google Cloud Architect Handbook: Designing highly available and resilient architectures on Google Cloud
Generative AI with Kubernetes: Implementing secure and observable AI infrastructure to deliver reliable AI applications
Data Analysis with LLMs: Text, tables, images and sound
Linear Parameter-Varying Control: Theory and Application to Automotive Systems