Title: Data Independence: Reclaiming Privacy in an Era of Evolving Tech, Author: Wes Chaar
Title: Math and Architectures of Deep Learning, Author: Krishnendu Chaudhury
Title: Machine Learning in Production: From Models to Products, Author: Christian Kastner
Title: Causal Inference for Data Science, Author: Alex Ruiz de Villa
Title: Data Governance: The Definitive Guide: People, Processes, and Tools to Operationalize Data Trustworthiness, Author: Evren Eryurek
Title: Fundamentals of Machine Learning for Predictive Data Analytics, second edition: Algorithms, Worked Examples, and Case Studies, Author: John D. Kelleher
Title: AI at the Edge: Solving Real-World Problems with Embedded Machine Learning, Author: Daniel Situnayake
Title: Algorithms for Decision Making, Author: Mykel J. Kochenderfer
Title: Managing Machine Learning Projects: From design to deployment, Author: Simon Thompson
Title: Outlier Detection in Python, Author: Brett Kennedy
Title: Reliable Machine Learning: Applying SRE Principles to ML in Production, Author: Cathy Chen
Title: Learning Theory from First Principles, Author: Francis Bach
Title: Graph Algorithms for Data Science: With examples in Neo4j, Author: Tomaz Bratanic
Title: The Shape of Data: Geometry-Based Machine Learning and Data Analysis in R, Author: Colleen M. Farrelly
Title: Machine Learning and Data Science Blueprints for Finance: From Building Trading Strategies to Robo-Advisors Using Python, Author: Hariom Tatsat
Title: Patterns, Predictions, and Actions: Foundations of Machine Learning, Author: Moritz Hardt
Title: Machine Learning Engineering in Action, Author: Ben Wilson
Title: Human-in-the-Loop Machine Learning: Active learning and annotation for human-centered AI, Author: Robert (Munro) Monarch
Title: Multi-Agent Reinforcement Learning: Foundations and Modern Approaches, Author: Stefano V. Albrecht
Title: Machine Learning Algorithms in Depth, Author: Vadim Smolyakov

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