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MACHINE LEARNING & AI BEYOND THE BASICS

Name: MACHINE LEARNING & AI BEYOND THE BASICS
Brand: NO STARCH
SKU: 9781718503762
Price: 14143 HUF
Availability: InStock

Szerző: RASCHKA SEBASTIAN

Nyelv:

Kötés: Puha kötésű

Kiadó: NO STARCH

Elérhetőség: Beszállítói készleten alacsony példányszámban

Küldés 12-17 napon belül

14 143 Ft

If you''ve locked down the basics of machine learning and AI and want a fun way to address lingering...

Információk a könyvről

Szerző

RASCHKA SEBASTIAN

Nyelv

Angol

Kötés

Könyv - Puha kötésű

Kiadva

2024

oldal

234

EAN

9781718503762

Enbook ID

44329190

Kiadó

NO STARCH

Súly

508

Teljes leírás

If you''ve locked down the basics of machine learning and AI and want a fun way to address lingering knowledge gaps, this book is for you. This rapid-fire series of short chapters addresses 30 essential questions in the field, helping you stay current on the latest technologies you can implement in your own work. Each chapter of Machine Learning and AI Beyond the Basics asks and answers a central question, with diagrams to explain new concepts and ample references for further reading. This practical, cutting-edge information is missing from most introductory coursework, but critical for real-world applications, research, and acing technical interviews. You won''t need to solve proofs or run code, so this book is a perfect travel companion. You''ll learn a wide range of new concepts in deep neural network architectures, computer vision, natural language processing, production and deployment, and model evaluation, including how to: Reduce overfitting with altered data or model modifications; Handle common sources of randomness when training deep neural networks; Speed up model inference through optimization without changing the model architecture or sacrificing accuracy; Practically apply the lottery ticket hypothesis and the distributional hypothesis; Use and finetune pretrained large language models; Set up k-fold cross-validation at the appropriate time. You''ll also learn to distinguish between self-attention and regular attention; name the most common data augmentation techniques for text data; use various self-supervised learning techniques, multi-GPU training paradigms, and types of generative AI; and much more. Whether you''re a machine learning beginner or an experienced practitioner, add new techniques to your arsenal and keep abreast of exciting developments in a rapidly changing field.

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MACHINE LEARNING & AI BEYOND THE BASICS

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