A01=Nicole Koenigstein
Author_Nicole Koenigstein
Category=KJT
Category=UFL
Category=UYD
Category=UYF
Category=UYQL
Category=UYQM
eq_bestseller
eq_business-finance-law
eq_computing
eq_isMigrated=1
eq_isMigrated=2
eq_new_release
eq_nobargain
eq_non-fiction
Transformers deep learning image classification segmentation and generation audio and video classification time series anomaly detection reinforcement learning model optimization and montitoring multimodal models foundation models
Product details
- ISBN 9781098167011
- Publication Date: 10 Apr 2026
- Publisher: O'Reilly Media
- Publication City/Country: US
- Product Form: Paperback
Secure
checkout
Fast Shipping
Easy returns
The vast potential of AI technology remains untapped in areas like audio, video, and complex data analysis. In fact, many of today's professionals find it challenging to apply AI innovations across these diverse domains due to a lack of comprehensive guidance and practical implementations.
This comprehensive guide, tailored especially for intermediate to advanced ML engineers, data scientists, and researchers, fills the gap. Author Nicole Koenigstein guides readers through the versatile applications of transformer models, not only deepening theoretical understanding but also emphasizing actionable strategies for real-world applications.
You'll discover how to:
- Apply transformers in nontext domains like image and music generation
- Optimize GPU usage and model training times
- Deploy and monitor transformer models effectively in production environments
- Utilize libraries such as Ray Tune and Optuna for advanced model tuning
Nicole is a distinguished data scientist and quantitative researcher, currently working as chief data scientist and head of AI and quantitative research for Wyden Capital, an algorithmic-based investment company, and as head of AI and quantitative research at quantmate, an innovative FinTech startup focused on alternative data in predictive modeling. Alongside her roles in these organizations, she serves as an AI consultant across a broad spectrum of AI applications, ranging from natural language processing, time series data, image classification and segmentation, to anomaly detection and beyond. She leads workshops and guides companies from the conceptual stages of AI implementation through to final deployment.
