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Mathematical theory of computation Books

Displaying results 1-48 of 9,629
Swim Training Patterns
Swim Training Patterns
by Christoph Bartneck
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Practical Weak Supervision
Practical Weak Supervision
by Amit Bahree, Senja Filipi and Wee Hyong Tok
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Practical Fairness
Practical Fairness
by Aileen Nielsen
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Reinforcement Learning
Reinforcement Learning
by Phil Winder
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Godel, Escher, Bach
Godel, Escher, Bach
by Douglas R. Hofstadter
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The Delicate Art of Brute Force
The Delicate Art of Brute Force
by Paul J. Nahin
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The Irrational Decision
The Irrational Decision
by Benjamin Recht
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Beading With Algorithms: Cellular Automata In Peyote Stitch
Beading With Algorithms: Cellular Automata In Peyote Stitch
by Gwen Fisher, Roger Antonsen and Zelda Lin
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Beading With Algorithms: Cellular Automata In Peyote Stitch
Beading With Algorithms: Cellular Automata In Peyote Stitch
by Gwen Fisher, Roger Antonsen and Zelda Lin
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History of Artificial Intelligence
History of Artificial Intelligence
by Abbas Tcharkhtchi, Hamid Reza Vanaei and Sofiane Khelladi
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Hands-On Machine Learning with Scikit-Learn and PyTorch
Hands-On Machine Learning with Scikit-Learn and PyTorch
by Aurelien Geron
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Introduction to Modern Cryptography
Introduction to Modern Cryptography
by Jonathan Katz and Yehuda Lindell
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AI Value Creators
AI Value Creators
by Dario Gil
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Designing Large Language Model Applications
Designing Large Language Model Applications
by Suhas Pai
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AI Engineering
AI Engineering
by Chip Huyen
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Hands-On Generative AI with Transformers and Diffusion Models
Hands-On Generative AI with Transformers and Diffusion Models
by Omar Sanseviero, Pedro Cuenca, Apolinario Passos and Jonathan Whitaker
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Machine Learning Production Systems
Machine Learning Production Systems
by Robert Crowe, Hannes Hapke, Emily Caveness and Di Zhu
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Learning Systems Thinking
Learning Systems Thinking
by Diana Montalion
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Prompt Engineering for Generative AI
Prompt Engineering for Generative AI
by James Phoenix and Mike Taylor
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Effective Machine Learning Teams
Effective Machine Learning Teams
by David Tan, Ada Leung and David Colls
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Machine Learning Interviews
Machine Learning Interviews
by Susan Shu Chang
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Generative Deep Learning
Generative Deep Learning
by David Foster
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Applied Machine Learning and AI for Engineers
Applied Machine Learning and AI for Engineers
by Jeff Prosise
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Designing Autonomous AI
Designing Autonomous AI
by Kence Anderson
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AI-Powered Business Intelligence
AI-Powered Business Intelligence
by Tobias Zwingmann
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Fundamentals of Deep Learning
Fundamentals of Deep Learning
by Nithin Buduma, Nikhil Buduma and Joe Papa
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Designing Machine Learning Systems
Designing Machine Learning Systems
by Chip Huyen
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Practical MLOps
Practical MLOps
by Noah Gift and Alfredo Deza
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AI and Machine Learning for on-Device Development
AI and Machine Learning for on-Device Development
by Laurence Moroney
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Introduction to Modern Cryptography
Introduction to Modern Cryptography
by Jonathan Katz and Yehuda Lindell
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Machine Learning and Data Science Blueprints for Finance
Machine Learning and Data Science Blueprints for Finance
by Hariom Tatsat, Sahil Puri and Brad Lookabaugh
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Practical AI on the Google Cloud Platform
Practical AI on the Google Cloud Platform
by Micheal Lanham
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Machine Learning Design Patterns
Machine Learning Design Patterns
by Valliappa Lakshmanan, Sara Robinson and Michael Munn
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Artificial Intelligence in Finance
Artificial Intelligence in Finance
by Yves J. Hilpisch
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AI and Machine Learning for Coders
AI and Machine Learning for Coders
by Laurence Moroney
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Deep Learning for Coders with Fastai and Pytorch
Deep Learning for Coders with Fastai and Pytorch
by Sylvain Gugger and Jeremy Howard
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Building Machine Learning Pipelines
Building Machine Learning Pipelines
by Hannes Hapke and Catherine Nelson
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The AI Ladder
The AI Ladder
by Rob Thomas and Paul Zikopoulos
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Building Machine Learning Powered Applications
Building Machine Learning Powered Applications
by Emmanuel Ameisen
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Practical Time Series Analysis
Practical Time Series Analysis
by Aileen Nielsen
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Building Intelligent Cloud Applications
Building Intelligent Cloud Applications
by John Biggs and Vicente Herrera García
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Deep Learning from Scratch
Deep Learning from Scratch
by Seth Weidman
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Machine Learning Pocket Reference
Machine Learning Pocket Reference
by Matt Harrison
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AI for People and Business
AI for People and Business
by Alex Castrounis
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Deep Learning for the Life Sciences
Deep Learning for the Life Sciences
by Karl Leswing, Peter Eastman, Vijay Pande and Bharath Ramsundar
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Feature Engineering for Machine Learning
Feature Engineering for Machine Learning
by Alice Zheng and Amanda Casari
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Spark: the Definitive Guide
Spark: the Definitive Guide
by Bill Chambers and Matei Zaharia
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Introduction to Machine Learning with Python
Introduction to Machine Learning with Python
by Sarah Guido and Andreas C. Müller
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