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: PyTorch Cookbook, Author: Matthew Rosch
Title: Deep Learning for Search, Author: Tommaso Teofili
Title: Mastering PyTorch: Create and deploy deep learning models from CNNs to multimodal models, LLMs, and beyond, Author: Ashish Ranjan Jha
Title: Pricing Options with Futures-Style Margining: A Genetic Adaptive Neural Network Approach, Author: Alan White
Title: Natural Language Processing in Action: Understanding, analyzing, and generating text with Python, Author: Hannes Hapke
Title: NONLINEAR ALGEBRA IN AN ACORN: With Applications to Deep Learning, Author: Martin J Lee
Title: Data Augmentation with Python: Enhance deep learning accuracy with data augmentation methods for image, text, audio, and tabular data, Author: Duc Haba
Title: Machine Learning Engineering with Python: Manage the lifecycle of machine learning models using MLOps with practical examples, Author: Andrew P. McMahon
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: Enhancing Deep Learning with Bayesian Inference: Create more powerful, robust deep learning systems with Bayesian deep learning in Python, Author: Matt Benatan
Title: Deep Learning with R, Author: François Chollet
Title: Hands-On Generative Adversarial Networks with PyTorch 1.x: Implement next-generation neural networks to build powerful GAN models using Python, Author: John Hany
Title: Machine Learning with R, the tidyverse, and mlr, Author: Hefin Rhys
Title: Python Machine Learning - Second Edition: Unlock modern machine learning and deep learning techniques with Python by using the latest cutting-edge open source Python libraries., Author: Sebastian Raschka

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