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Deep Learning at Scale: At the Intersection of Hardware, Software, and Data - Paperback
$79.99
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by Suneeta Mall (Author)
Bringing a deep-learning project into production at scale is quite challenging. To successfully scale your project, a foundational understanding of full stack deep learning, including the knowledge that lies at the intersection of hardware, software, data, and algorithms, is required.
This book illustrates complex concepts of full stack deep learning and reinforces them through hands-on exercises to arm you with tools and techniques to scale your project. A scaling effort is only beneficial when it's effective and efficient. To that end, this guide explains the intricate concepts and techniques that will help you scale effectively and efficiently.
You'll gain a thorough understanding of:
- How data flows through the deep-learning network and the role the computation graphs play in building your model
- How accelerated computing speeds up your training and how best you can utilize the resources at your disposal
- How to train your model using distributed training paradigms, i.e., data, model, and pipeline parallelism
- How to leverage PyTorch ecosystems in conjunction with NVIDIA libraries and Triton to scale your model training
- Debugging, monitoring, and investigating the undesirable bottlenecks that slow down your model training
- How to expedite the training lifecycle and streamline your feedback loop to iterate model development
- A set of data tricks and techniques and how to apply them to scale your training model
- How to select the right tools and techniques for your deep-learning project
- Options for managing the compute infrastructure when running at scale
Number of Pages: 448Dimensions: 0.91 x 9.19 x 7 INIllustrated: YesPublication Date: July 23, 2024
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Standard U.S. returns are accepted for eligible new, unopened items within 30 days of carrier delivery. Returns are by mail. Customers are responsible for standard return shipping, there is no restocking fee, and standard exchanges are not offered. Once an approved return is received and inspected, the refund is issued to the original payment method within 5 business days. Damaged, defective, or incorrect items are handled at no return-shipping cost to the customer.
Return eligibility is subject to the full policy. Opened, read, or unsealed books with broken seals or visible wear are final sale. Digital downloads, gift cards, and personalized products are non-refundable. Original shipping charges are not refunded for standard returns. Contact us within 7 days of delivery about damaged, defective, or incorrect items.
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