Title: Machine Learning with PyTorch and Scikit-Learn: Develop machine learning and deep learning models with Python, Author: Sebastian Raschka
Title: Practical C++ Machine Learning: Hands-on strategies for developing simple machine learning models using C++ data structures and libraries, Author: Anais Sutherland
Title: Statistics with Rust, Second Edition: Explore rust programming and its powerful crates across data science, machine learning and NLP projects, Author: Keiko Nakamura
Title: Graph Algorithms the Fun Way: Powerful Algorithms Decoded, Not Oversimplified, Author: Jeremy Kubica
Title: Pytorch Deep Learning by Example (2nd Edition), Author: Benjamin Young
Title: Machine Learning with Rust: A practical attempt to explore Rust and its libraries across popular machine learning techniques, Author: Keiko Nakamura
Title: Deep Learning with R, Second Edition, Author: Francois Chollet
Title: Angular and Machine Learning Pocket Primer, Author: Oswald Campesato
Title: 10 Machine Learning Blueprints You Should Know for Cybersecurity: Protect your systems and boost your defenses with cutting-edge AI techniques, Author: Rajvardhan Oak
Title: Google JAX Cookbook: Perform machine learning and numerical computing with combined capabilities of TensorFlow and NumPy, Author: Zephyr Quent
Title: Evolutionary Deep Learning: Genetic algorithms and neural networks, Author: Micheal Lanham
Title: Deep Learning with MXNet Cookbook: Discover an extensive collection of recipes for creating and implementing AI models on MXNet, Author: Andrés P. Torres
Title: Algorithmic Short Selling with Python: Refine your algorithmic trading edge, consistently generate investment ideas, and build a robust long/short product, Author: Laurent Bernut
Title: Applied Deep Learning and Computer Vision for Self-Driving Cars: Build autonomous vehicles using deep neural networks and behavior-cloning techniques, Author: Sumit Ranjan
Title: Multi-Agent Reinforcement Learning: Foundations and Modern Approaches, Author: Stefano V. Albrecht
Title: Modern Computer Vision with PyTorch: Explore deep learning concepts and implement over 50 real-world image applications, Author: V Kishore Ayyadevara
Title: PyTorch Cookbook, Author: Matthew Rosch
Title: Deep Learning with Keras from Scratch, Author: Benjamin Young
Title: Neural Networks with R: Uncover the power of artificial neural networks by implementing them through R code., Author: Giuseppe Ciaburro
Title: Grokking Deep Learning, Author: Andrew W. Trask

Pagination Links