Title: Machine Learning with PyTorch and Scikit-Learn: Develop machine learning and deep learning models with Python, Author: Sebastian Raschka
Title: Gradient Expectations: Structure, Origins, and Synthesis of Predictive Neural Networks, Author: Keith L. Downing
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: TensorFlow????????: Chinese Edition, Author: Posts & Telecom Press
Title: PyTorch Cookbook: 100+ Solutions across RNNs, CNNs, python tools, distributed training and graph networks, Author: Matthew Rosch
Title: Python??????????: Chinese Edition, Author: Posts & Telecom Press
Title: Evolutionary Deep Learning: Genetic algorithms and neural networks, Author: Micheal Lanham
Title: ??????: Chinese Edition, Author: Posts & Telecom Press
Title: ????????: Chinese Edition, Author: Posts & Telecom Press
Title: TensorFlow????????: Chinese Edition, Author: Posts & Telecom Press
Title: TensorFlow????: Chinese Edition, Author: Posts & Telecom Press
Title: Python????: Chinese Edition, Author: Posts & Telecom Press
Title: ?????Python??(?2?): Chinese Edition, Author: Posts & Telecom Press
Title: Deep Learning with R, Second Edition, Author: Francois Chollet
Title: Managing Machine Learning Projects: From design to deployment, Author: Simon Thompson
Title: ????????: Chinese Edition, Author: Posts & Telecom Press
Title: Deep Learning with Keras from Scratch, Author: Benjamin Young

Pagination Links