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Practical MLOps - by Noah Gift & Alfredo Deza (Paperback)

Explainable AI for Practitioners - by Michael Munn & David Pitman (Paperback)

Llms and Generative AI for Healthcare - by Kerrie Holley & Manish Mathur (Paperback)

R for Data Science - 2nd Edition by Hadley Wickham & Mine Cetinkaya-Rundel & Garrett Grolemund (Paperback)

SQL for Data Analysis - by Cathy Tanimura (Paperback)

Training Data for Machine Learning - by Anthony Sarkis (Paperback)

Python for Data Analysis - 3rd Edition by Wes McKinney (Paperback)

Football Analytics with Python & R - by Eric A Eager & Richard a Erickson (Paperback)

Learning Github Copilot - by Brent Laster (Paperback)

Eloquent Javascript, 4th Edition - by Marijn Haverbeke (Paperback)

Learning Microsoft Power Bi - by Jeremey Arnold (Paperback)

Coding Projects in Python - (DK Help Your Kids) by DK (Paperback)

Building Machine Learning Systems with a Feature Store - by Jim Dowling (Paperback)

Delta Lake: The Definitive Guide - by Denny Lee & Tristen Wentling & Scott Haines & Prashanth Babu (Paperback)

Essential Math for Data Science - by Thomas Nield (Paperback)

Thinking with Data - by Max Shron (Paperback)

Data Modeling with Microsoft Power BI - by Markus Ehrenmueller-Jensen (Paperback)

Hands-On APIs for AI and Data Science - by Ryan Day (Paperback)

Deep Learning for Biology - by Charles Ravarani & Natasha Latysheva (Paperback)

Transformers: The Definitive Guide - by Nicole Koenigstein (Paperback)

Practical Tableau - by Ryan Sleeper (Paperback)

Reinforcement Learning for Finance - by Yves Hilpisch (Paperback)

Prompt Engineering for Llms - by John Berryman & Albert Ziegler (Paperback)

AI and Machine Learning for On-Device Development - by Laurence Moroney (Paperback)