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Machine Learning for Robotics (First Early Release) - Farid - 09-10-2023
![[Image: 6XaRv4.pbka9azr463v.png]](https://i.im.ge/2023/09/10/6XaRv4.pbka9azr463v.png)
Machine Learning for Robotics | Alishba Imran and Keerthana Gopalakrishnan | 2023 | O'Reilly Media, Inc |
Machine learning is the present and future of robotics, whether for self-driving vehicles, consumer robotics, or industrial manufacturing. Driven by breakthroughs in research and compute infrastructure, widespread deployment of huge neural nets, and end-to-end robotics tasks, the science and practice of robotics is in the midst of disruption from data-driven approaches such as deep learning and foundational models. If you're a software or machine learning engineer looking to get into robotics, or a robotics engineer looking to deploy machine learning in your projects, this is your book.
Machine learning is the present and future of robotics, whether it's for self-driving vehicles, consumer robotics, or industrial manufacturing. Driven by breakthroughs in research and compute infrastructure, widespread deployment of huge neural nets, and end-to-end robotics tasks, the science and practice of robotics is in the midst of disruption from data-driven approaches such as deep learning and foundation models.
If you're a software or machine learning engineer looking to get into robotics, or a robotics engineer planning to deploy machine learning in your projects, this is your book.
You'll learn how to apply deep learning methods to robotics and approach core robotics technologies-perception, reasoning, and prediction-from a deep learning perspective. This guide explores state-of-the-art deep learning algorithms relevant to each core technology and shows you how to use them for real-world robotics. Relevant code samples demonstrate how to apply these algorithms.
You'll learn how to
Formulate robotics as a data-driven AI problem
Recognize the technology behind designing and deploying modern robotics: sensing, perception, training, and control
Apply state-of-the-art techniques in AI to robotics systems
Understand factors driving decision-making in technical design for several robotics applications
Design practical robotic systems for real-world applications: self-driving, prosthetics, and industrial automation
Contents of Download:
Machine Learning for Robotics.epub (7.08 MB)
Machine Learning for Robotics.mobi (1.92 MB)
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