Title: Graph Algorithms the Fun Way: Powerful Algorithms Decoded, Not Oversimplified, Author: Jeremy Kubica
Title: Deep Learning: A Visual Approach, Author: Andrew Glassner
Title: Practical Deep Learning: A Python-Based Introduction, Author: Ronald T. Kneusel
Title: Graph Neural Networks in Action, Author: Keita Broadwater
Title: Natural Language Processing in Action, Second Edition, Author: Hobson Lane
Title: Math and Architectures of Deep Learning, Author: Krishnendu Chaudhury
Title: Machine Learning with PyTorch and Scikit-Learn: Develop machine learning and deep learning models with Python, Author: Sebastian Raschka
Title: Deep Learning with JAX, Author: Grigory Sapunov
Title: Evolutionary Deep Learning: Genetic algorithms and neural networks, Author: Micheal Lanham
Title: Perceptrons, Reissue of the 1988 Expanded Edition with a new foreword by Léon Bottou: An Introduction to Computational Geometry, Author: Marvin Minsky
Title: Bayesian Optimization in Action, Author: Quan Nguyen
Title: Pulsed Neural Networks, Author: Wolfgang Maass
Title: Deep Learning with R, Second Edition, Author: Francois Chollet
Title: Inside Deep Learning: Math, Algorithms, Models, Author: Edward Raff
Title: TensorFlow for Deep Learning: From Linear Regression to Reinforcement Learning, Author: Bharath Ramsundar
Title: Self-Organizing Maps / Edition 3, Author: Teuvo Kohonen
Title: Deep Learning and the Game of Go, Author: Max Pumperla
Title: Introduction to EEG- and Speech-Based Emotion Recognition, Author: Priyanka A. Abhang
Title: Common LISP Modules: Artificial Intelligence in the Era of Neural Networks and Chaos Theory / Edition 1, Author: Mark Watson
Title: Automatic Modulation Recognition of Communication Signals / Edition 1, Author: Elsayed Azzouz

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