Title: Ultimate Parallel and Distributed Computing with Julia For Data Science: Excel in Data Analysis, Statistical Modeling and Machine Learning by leveraging MLBase.jl and MLJ.jl to optimize workflows (English Edition), Author: Nabanita Dash
Title: The Little Learner: A Straight Line to Deep Learning, Author: Daniel P. Friedman
Title: How Large Language Models Work, Author: Edward Raff
Title: Fundamentals of Machine Learning for Predictive Data Analytics, second edition: Algorithms, Worked Examples, and Case Studies, Author: John D. Kelleher
Title: Managing Machine Learning Projects: From design to deployment, Author: Simon Thompson
Title: TensorFlow 2 Pocket Reference: Building and Deploying Machine Learning Models, Author: KC Tung
Title: Learning Pandas 2.0: A Comprehensive Guide to Data Manipulation and Analysis for Data Scientists and Machine Learning Professionals, Author: Matthew Rosch
Title: Graph Neural Networks in Action, Author: Keita Broadwater
Title: Machine Learning con Python - Nuova edizione: Costruire algoritmi per generare conoscenza, Author: Sebastian Raschka
Title: Learning TensorFlow.js, Author: Gant Laborde
Title: TensorFlow Developer Certification Guide, Author: Patrick J
Title: Machine Learning with TensorFlow, Second Edition, Author: Chris Mattmann
Title: Distributed Machine Learning Patterns, Author: Yuan Tang
Title: AI for Knowledge, Author: Andrew Cox
Explore Series
Title: Machine Learning spiegato in modo facile: Guida illustrata per programmatori curiosi, Author: Luis G. Serrano
Title: Machine Learning Bookcamp: Build a portfolio of real-life projects, Author: Alexey Grigorev
Title: Introducing Data Science: Big data, machine learning, and more, using Python tools, Author: Davy Cielen
Title: Machine Learning with SAS Viya, Author: SAS Institute Inc.
Title: Math for Deep Learning: What You Need to Know to Understand Neural Networks, Author: Ronald T. Kneusel
Title: Spark GraphX in Action, Author: Michael Malak

Pagination Links